Senior Software Engineering Jobs in North Carolina
Senior Software Engineering jobs in North Carolina are in strong and sustained demand, concentrated in enterprise software, fintech, healthcare technology, and cloud infrastructure across a market that hires from associate-level through principal and staff engineer. The Triangle region anchors hiring, with Raleigh and Durham leading, followed by Charlotte and the growing tech corridor around Cary and Research Triangle Park, where companies like Red Hat, Fidelity Investments, and Lenovo maintain significant engineering operations. Distributed systems, backend platform engineering, and cloud-native development are the most consistently sought specialties. Find a role that fits below and apply directly.
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Showing 5 of 12+ Senior Software Engineering jobs
About this role:
Wells Fargo is seeking a Software Engineering Senior Manager – Quantitative Data & Analytics to lead a team of engineering professionals supporting the modernization and transformation of the Wealth & Investment Management (WIM) analytics ecosystem. This leader will be responsible for building and developing a high-performing engineering organization focused on delivering scalable, secure, and reliable data solutions that power enterprise reporting, analytics, and business intelligence capabilities.
You will provide strategic direction for data engineering initiatives, drive modernization of legacy platforms, establish governance and engineering best practices, and partner closely with business and technology leaders to deliver high-value solutions. You will also lead the build-out of an AI context layer (the semantic layer, business ontology, and context library that gives AI tools and analysts a trusted, governed understanding of analytics data). You will oversee the large-scale data and analytics platforms that power it.
The ideal candidate will possess strong people leadership skills, deep technical expertise in data engineering, and the ability to execute complex initiatives while developing talent and fostering a culture of innovation, accountability, and continuous improvement.
In this role, you will:
- Manage, coach, and develop a team or teams of experienced data engineers and engineering managers in roles with moderate complexity and risk, and support of enterprise data solutions.
- Ensure adherence to the Banking Platform Architecture, and meeting non-functional requirements with each release
- Partner with, engage and influence architects and experienced engineers to incorporate Wells Fargo Technology technical strategies, while understanding next generation domain architecture and enable application migration paths to target architecture; for example cloud readiness, application modernization, data strategy
- Establish and execute strategic priorities that align data engineering capabilities with business objectives and long-term technology roadmaps.
- Drive modernization efforts by transforming legacy reporting and data-processing environments into scalable, governed, and reusable data platforms.
- Oversee the design and implementation of enterprise-scale data pipelines, data models, data integration solutions, and analytics platforms.
- Lead the design and build-out of an AI context layer (semantic layer, business ontology, context library, and governed metadata). It should let AI assistants, agents, and self-service users work with WIM data accurately and safely, and support change impact analysis.
- Operate and continuously improve large-scale data and analytics platforms, with clear standards for reliability, performance, observability, and cost.
- Evaluate and adopt new AI and data tools, such as AI-assisted engineering, automated metadata harvesting, and ontology and knowledge graph platforms, to accelerate delivery and scale the context layer.
- Ensure engineering standards, controls, governance practices, and operational processes are consistently applied across the organization.
- Partner with technology leaders, architects, product owners, and business stakeholders to prioritize work, define requirements, and deliver business outcomes.
- Lead resource planning, workload management, budget oversight, and talent development initiatives to support organizational goals.
- Identify opportunities to improve efficiency, reduce technical debt, eliminate redundant data assets, and optimize data processing capabilities.
- Drive adoption of modern data engineering practices, including data orchestration, automation, monitoring, and cloud-based technologies.
- Ensure compliance with enterprise risk, security, data management, and regulatory requirements.
- Manage delivery of multiple initiatives while balancing competing priorities, deadlines, and stakeholder expectations.
- Foster a culture of collaboration, innovation, inclusion, and continuous learning across the team.
- Interpret, develop and ensure security, stability, and scalability within functions of technology with moderate complexity, as well as identify, manage and mitigate technology and enterprise risk
- Collaborate with, partner with and influence Product Managers/Product Owners to drive user satisfaction, influence technology requirements and priorities in the product roadmap, promote innovative and intelligent solutions, generate corporate value and articulate technical strategy while being a solid advocate of agile and DevOps practices
- Manage allocation of people and financial resources to ensure commitments are met and align with strategic objectives in technology engineering
- Hire, build and guide a culture of talent development to have the skills required to effectively design and deliver innovative solutions for product areas and products to meet business objectives and strategy, as well as conduct performance management for engineers and managers
Required Qualifications:
- 7+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- 7+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, or education.
- 3+ years of management or leadership experience
- 3+ years of experience operating large-scale enterprise data and analytics platforms (for example, data warehouses, data lakes or lakehouses, ETL/ELT pipelines, and BI environments)
- 2+ years of experience using modern data and AI tools to build AI context layers (for example, semantic layers, business ontologies, knowledge graphs, or governed metadata) that ground AI and analytics solutions in enterprise data
Desired Qualifications:
- Experience building an enterprise AI context layer (semantic layer, business ontology, context library, and governed, versioned business definitions) that gives AI assistants, agents, and analysts a trusted, consistent view of enterprise data.
- Experience designing business ontologies and knowledge graphs for financial services domains
- Experience with metadata management, business glossaries, data catalogs, and lineage tools and using that metadata to power AI context and change impact analysis.
- Experience using emerging AI tools to accelerate data engineering and ontology development, such as AI coding assistants, automated metadata harvesting, and LLM-assisted semantic mapping and documentation. Experience grounding generative AI, agents, and natural-language analytics in enterprise data using techniques such as retrieval-augmented generation (RAG), GraphRAG, vector search, and Model Context Protocol (MCP), including testing outputs for accuracy.
- Experience running large-scale data and analytics platforms in production, including observability, SLAs, incident and problem management, capacity planning, and cost optimization.
- Knowledge of responsible AI, model risk, and data privacy practices for AI solutions in financial services, including controlling what data AI tools can access.
- Experience leading enterprise data modernization, analytics transformation, or large-scale reporting platform initiatives.
- Experience with cloud-based data platforms and modern data architectures.
- Experience with enterprise data lake, data warehouse, ETL/ELT, and data orchestration technologies.
- Experience supporting business intelligence and analytics platforms such as Power BI, Tableau, or similar technologies.
- Knowledge of financial services data environments, governance standards, and regulatory requirements.
- Experience developing reusable and governed data assets that support self-service analytics.
- Experience with Agile delivery methodologies and product-based technology organizations.
- Experience implementing data governance, data quality, risk management, and operational controls.
- Proven ability to build, lead, and retain high-performing teams.
- Strong executive presence and ability to communicate effectively with senior leadership.
- Bachelor's degree or higher in Computer Science, Information Systems, Engineering, Data Science, or a related field
- Ability to influence, collaborate, and build relationships across multiple levels of the organization.
- Experience partnering with business and technology stakeholders to deliver strategic initiatives and technology solutions.
- Experience leading teams responsible for the design, development, and implementation of enterprise data solutions.
- Experience building and supporting large-scale data pipelines, data integration frameworks, and data platforms.
- Experience with data modeling, database technologies, data warehousing, and enterprise reporting architectures.
- Experience managing multiple priorities, complex projects, and technology deliverables in a fast-paced environment.
- Strong leadership, communication, relationship management, and organizational skills.
Job Expectations:
- This position offers a hybrid work schedule - ability to work in office
- This position is not eligible for Visa sponsorship
- Relocation assistance is not available for this position
Posting End Date:
28 Sep 2026- Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
About this role:
Wells Fargo is seeking a Software Engineering Senior Manager – Quantitative Data & Analytics to lead a team of engineering professionals supporting the modernization and transformation of the Wealth & Investment Management (WIM) analytics ecosystem. This leader will be responsible for building and developing a high-performing engineering organization focused on delivering scalable, secure, and reliable data solutions that power enterprise reporting, analytics, and business intelligence capabilities.
You will provide strategic direction for data engineering initiatives, drive modernization of legacy platforms, establish governance and engineering best practices, and partner closely with business and technology leaders to deliver high-value solutions. You will also lead the build-out of an AI context layer (the semantic layer, business ontology, and context library that gives AI tools and analysts a trusted, governed understanding of analytics data). You will oversee the large-scale data and analytics platforms that power it.
The ideal candidate will possess strong people leadership skills, deep technical expertise in data engineering, and the ability to execute complex initiatives while developing talent and fostering a culture of innovation, accountability, and continuous improvement.
In this role, you will:
- Manage, coach, and develop a team or teams of experienced data engineers and engineering managers in roles with moderate complexity and risk, and support of enterprise data solutions.
- Ensure adherence to the Banking Platform Architecture, and meeting non-functional requirements with each release
- Partner with, engage and influence architects and experienced engineers to incorporate Wells Fargo Technology technical strategies, while understanding next generation domain architecture and enable application migration paths to target architecture; for example cloud readiness, application modernization, data strategy
- Establish and execute strategic priorities that align data engineering capabilities with business objectives and long-term technology roadmaps.
- Drive modernization efforts by transforming legacy reporting and data-processing environments into scalable, governed, and reusable data platforms.
- Oversee the design and implementation of enterprise-scale data pipelines, data models, data integration solutions, and analytics platforms.
- Lead the design and build-out of an AI context layer (semantic layer, business ontology, context library, and governed metadata). It should let AI assistants, agents, and self-service users work with WIM data accurately and safely, and support change impact analysis.
- Operate and continuously improve large-scale data and analytics platforms, with clear standards for reliability, performance, observability, and cost.
- Evaluate and adopt new AI and data tools, such as AI-assisted engineering, automated metadata harvesting, and ontology and knowledge graph platforms, to accelerate delivery and scale the context layer.
- Ensure engineering standards, controls, governance practices, and operational processes are consistently applied across the organization.
- Partner with technology leaders, architects, product owners, and business stakeholders to prioritize work, define requirements, and deliver business outcomes.
- Lead resource planning, workload management, budget oversight, and talent development initiatives to support organizational goals.
- Identify opportunities to improve efficiency, reduce technical debt, eliminate redundant data assets, and optimize data processing capabilities.
- Drive adoption of modern data engineering practices, including data orchestration, automation, monitoring, and cloud-based technologies.
- Ensure compliance with enterprise risk, security, data management, and regulatory requirements.
- Manage delivery of multiple initiatives while balancing competing priorities, deadlines, and stakeholder expectations.
- Foster a culture of collaboration, innovation, inclusion, and continuous learning across the team.
- Interpret, develop and ensure security, stability, and scalability within functions of technology with moderate complexity, as well as identify, manage and mitigate technology and enterprise risk
- Collaborate with, partner with and influence Product Managers/Product Owners to drive user satisfaction, influence technology requirements and priorities in the product roadmap, promote innovative and intelligent solutions, generate corporate value and articulate technical strategy while being a solid advocate of agile and DevOps practices
- Manage allocation of people and financial resources to ensure commitments are met and align with strategic objectives in technology engineering
- Hire, build and guide a culture of talent development to have the skills required to effectively design and deliver innovative solutions for product areas and products to meet business objectives and strategy, as well as conduct performance management for engineers and managers
Required Qualifications:
- 7+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- 7+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, or education.
- 3+ years of management or leadership experience
- 3+ years of experience operating large-scale enterprise data and analytics platforms (for example, data warehouses, data lakes or lakehouses, ETL/ELT pipelines, and BI environments)
- 2+ years of experience using modern data and AI tools to build AI context layers (for example, semantic layers, business ontologies, knowledge graphs, or governed metadata) that ground AI and analytics solutions in enterprise data
Desired Qualifications:
- Experience building an enterprise AI context layer (semantic layer, business ontology, context library, and governed, versioned business definitions) that gives AI assistants, agents, and analysts a trusted, consistent view of enterprise data.
- Experience designing business ontologies and knowledge graphs for financial services domains
- Experience with metadata management, business glossaries, data catalogs, and lineage tools and using that metadata to power AI context and change impact analysis.
- Experience using emerging AI tools to accelerate data engineering and ontology development, such as AI coding assistants, automated metadata harvesting, and LLM-assisted semantic mapping and documentation. Experience grounding generative AI, agents, and natural-language analytics in enterprise data using techniques such as retrieval-augmented generation (RAG), GraphRAG, vector search, and Model Context Protocol (MCP), including testing outputs for accuracy.
- Experience running large-scale data and analytics platforms in production, including observability, SLAs, incident and problem management, capacity planning, and cost optimization.
- Knowledge of responsible AI, model risk, and data privacy practices for AI solutions in financial services, including controlling what data AI tools can access.
- Experience leading enterprise data modernization, analytics transformation, or large-scale reporting platform initiatives.
- Experience with cloud-based data platforms and modern data architectures.
- Experience with enterprise data lake, data warehouse, ETL/ELT, and data orchestration technologies.
- Experience supporting business intelligence and analytics platforms such as Power BI, Tableau, or similar technologies.
- Knowledge of financial services data environments, governance standards, and regulatory requirements.
- Experience developing reusable and governed data assets that support self-service analytics.
- Experience with Agile delivery methodologies and product-based technology organizations.
- Experience implementing data governance, data quality, risk management, and operational controls.
- Proven ability to build, lead, and retain high-performing teams.
- Strong executive presence and ability to communicate effectively with senior leadership.
- Bachelor's degree or higher in Computer Science, Information Systems, Engineering, Data Science, or a related field
- Ability to influence, collaborate, and build relationships across multiple levels of the organization.
- Experience partnering with business and technology stakeholders to deliver strategic initiatives and technology solutions.
- Experience leading teams responsible for the design, development, and implementation of enterprise data solutions.
- Experience building and supporting large-scale data pipelines, data integration frameworks, and data platforms.
- Experience with data modeling, database technologies, data warehousing, and enterprise reporting architectures.
- Experience managing multiple priorities, complex projects, and technology deliverables in a fast-paced environment.
- Strong leadership, communication, relationship management, and organizational skills.
Job Expectations:
- This position offers a hybrid work schedule - ability to work in office
- This position is not eligible for Visa sponsorship
- Relocation assistance is not available for this position
Posting End Date:
28 Sep 2026- Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
See All 12 Senior Software Engineering Jobs in North Carolina
Find roles in North Carolina that match your experience and apply in just a few clicks.
Find JobsSenior Software Engineering Jobs by City in North Carolina
Where North Carolina roles are concentrated, by current openings.
Senior Software Engineering Job Market in North Carolina
A snapshot from current North Carolina openings, updated as new roles post.
Who's Hiring
What North Carolina Employers Look For
The qualifications that appear most often in senior software engineering jobs across North Carolina.
- Bachelor's degree in computer science, software engineering, or a closely related field
- Five or more years of professional software development experience in production environments
- Proficiency in one or more languages such as Java, Python, Go, or C++
- Experience designing and deploying cloud-based systems on AWS, Azure, or Google Cloud
- Demonstrated ability to mentor junior engineers and lead technical design reviews
- Familiarity with agile development practices, CI/CD pipelines, and DevOps tooling
Senior Software Engineering Jobs in North Carolina: Frequently Asked Questions
How do you become a senior software engineering in North Carolina?
Reaching a senior software engineering role in North Carolina follows a path of progressive experience rather than a state-issued license. Most employers require a bachelor's degree in computer science or a related field, followed by several years building production systems. North Carolina's dense concentration of technology employers around Research Triangle Park means candidates often move up through mid-level roles at companies in fintech, healthcare IT, or enterprise software before earning the senior title.
How much do senior software engineerings make in North Carolina?
Senior software engineerings in North Carolina earn a median of about $134,710 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $83,840 for the lowest 10% to over $179,310 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior software engineerings in North Carolina?
Employers hiring senior software engineerings in North Carolina right now include Wells Fargo, CVS Health, and UDig, based on current listings on Migrate Mate as of September 2026. North Carolina's blend of major financial services firms in Charlotte and technology companies anchored around Research Triangle Park means senior engineering demand comes from a wide range of established industries.
Which North Carolina cities have the most senior software engineering jobs?
Charlotte, North Carolina, and Durham have the most senior software engineering openings in North Carolina. Raleigh and Durham lead because of the dense cluster of technology companies, university research spinoffs, and enterprise software firms anchored at and around Research Triangle Park, while Charlotte drives significant demand through its large financial services and banking sector, which has expanded its in-house engineering teams considerably in recent years.
Are there remote senior software engineering jobs in North Carolina?
Yes, and more than most fields. About 50% of senior software engineering openings tied to North Carolina are remote or hybrid as of September 2026, reflecting the desk-based and collaborative-but-asynchronous nature of the work. Backend platform roles, cloud infrastructure positions, and distributed systems engineering tend to be the most remote-compatible specialties among North Carolina postings.
How can I get hired as a senior software engineering in North Carolina with little or no experience?
The most realistic entry path is landing an associate or junior software engineer role at one of North Carolina's large technology or financial services employers, then building toward senior over several years. Companies like Red Hat, Fidelity Investments, and major health systems in the Triangle and Charlotte often run new-graduate and early-career programs. A strong portfolio of shipped projects, open-source contributions, or a relevant cloud certification gives candidates without extensive professional experience a concrete edge in a competitive market.
Where can I find and apply to senior software engineering jobs in North Carolina?
You can find and apply to senior software engineering jobs in North Carolina on Migrate Mate, which lists current openings across the state. Find roles that fit your experience and location preference and apply directly to the ones that match.
See All 12 Senior Software Engineering Jobs in North Carolina
Find roles in North Carolina that match your experience and apply in just a few clicks.
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