Senior Level Data Lead Jobs
Senior level data lead jobs place experienced professionals in charge of data strategy, analytics infrastructure, and the cross-functional teams that turn raw data into business decisions. Roles are concentrated in Technology & Software, Banking & Financial Services, and Investment & Asset Management, with a mix of on-site, remote, and hybrid settings, and employers like Rippling, Oracle, and JPMorganChase hiring at this level now.
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Join Mizuho as a Lead Data Engineer! We are seeking an experienced Lead Data Engineer with 7+ years of experience designing, building, and delivering scalable enterprise data solutions. The ideal candidate will be a strong hands-on engineer with deep expertise in Snowflake, Python, and Airflow, along with experience working in Azure or a comparable cloud platform. The role will be responsible for developing robust data pipelines and data platforms while contributing to technical architecture, engineering standards, performance, data quality, and production reliability. Experience with modern data platforms such as Databricks and Spark, as well as data governance and enterprise architecture principles, is highly desirable.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT frameworks supporting enterprise data and analytics workloads.
- Build and optimize data solutions using Snowflake, including data modeling, transformation, performance optimization, and workload management.
- Develop reusable and production-grade data engineering components using Python.
- Design and orchestrate complex workflows using Apache Airflow or similar orchestration platforms.
- Develop and support cloud-based data solutions using Microsoft Azure or comparable cloud technologies.
- Partner with business, analytics, architecture, governance, and technology teams to translate requirements into scalable technical solutions.
- Define technical designs, integration patterns, engineering standards, and best practices for enterprise data solutions.
- Implement appropriate data quality, monitoring, lineage, security, and operational controls across data pipelines.
- Troubleshoot production issues and drive improvements around performance, resiliency, scalability, and maintainability.
- Conduct design and code reviews and provide technical guidance to data engineering teams.
- Contribute to modernization of the data platform and adoption of modern engineering practices and technologies.
- Working experience in an Agile environment.
Required Qualifications
- 7+ years of professional experience in data engineering, data platforms, or related technology roles.
- Strong hands-on expertise with Snowflake & Star Schema Architecture.
- Advanced programming experience with Python & SQL.
- Strong experience with Apache Airflow or comparable workflow orchestration technologies.
- Hands-on experience with Microsoft Azure or another major cloud platform such as AWS or GCP.
- Strong experience designing and developing ETL/ELT pipelines, data integration solutions, and enterprise data processing workflows.
- Strong knowledge of SQL, data modeling, data warehousing, and performance optimization.
- Experience designing solutions for scalability, reliability, maintainability, and production support.
- Strong problem-solving, communication, and stakeholder-management skills.
- Ability to operate effectively in a complex enterprise environment and work across engineering, architecture, governance, and business teams.
Preferred Qualifications
- Experience with Databricks and Apache Spark.
- Experience with Azure Data Factory (ADF) and other Azure data services.
- Knowledge of data governance, metadata management, lineage, data quality, and access-control frameworks.
- Experience with enterprise data architecture and solution design.
- Understanding of modern architectural approaches such as lakehouse, medallion architecture, and cloud-native data platforms.
- Experience establishing engineering standards, reusable frameworks, and design patterns.
- Financial services or other highly regulated industry experience is a plus.
Ideal Candidate
The successful candidate combines strong hands-on data engineering capabilities with technical leadership. They should be comfortable moving between architecture and design discussions, hands-on engineering, technical problem-solving, and collaboration with business and technology stakeholders. The role is well suited for someone who can take ownership of complex data solutions from design through production while helping raise overall engineering standards across the team.
The expected base salary ranges from $112,000-$200,000. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, certifications and licenses obtained. Market and organizational factors are also considered. In addition to salary and a generous employee benefits package, including Medical, Dental and 401K plans, successful candidates are also eligible to receive a discretionary bonus.
Other Requirements
In office attendance is an essential function of this role. There is currently a requirement to be in the office a minimum 50% of the time, or five out of every 10 business days. Specific information about the requirements for your role will be communicated during the recruitment process.
Company Overview
Mizuho Financial Group, Inc. is the 15th largest bank in the world as measured by total assets of ~ $2 trillion. Mizuho's 60,000 employees worldwide offer comprehensive financial services to clients in 35 countries and 800 offices throughout the Americas, EMEA and Asia. Mizuho Americas is a leading provider of corporate and investment banking services to clients in the US, Canada, and Latin America. Through its acquisition of Greenhill, Mizuho provides M&A, restructuring and private capital advisory capabilities across Americas, Europe and Asia. Mizuho Americas employs approximately 3,500 professionals, and its capabilities span corporate and investment banking, capital markets, equity and fixed income sales & trading, derivatives, FX, custody and research.
We are an equal employment opportunity employer, and we comply with applicable laws prohibiting discrimination in all of the jurisdictions where we operate. AA Employer - M/F/Disability/Veteran. Accommodations are available upon request for applicants with disabilities and other covered reasons in accordance with applicable law. We participate in the E-Verify program. We maintain a drug-free workplace and reserve the right to require pre- and post-hire drug testing, as permitted by applicable law.
Join Mizuho as a Lead Data Engineer! We are seeking an experienced Lead Data Engineer with 7+ years of experience designing, building, and delivering scalable enterprise data solutions. The ideal candidate will be a strong hands-on engineer with deep expertise in Snowflake, Python, and Airflow, along with experience working in Azure or a comparable cloud platform. The role will be responsible for developing robust data pipelines and data platforms while contributing to technical architecture, engineering standards, performance, data quality, and production reliability. Experience with modern data platforms such as Databricks and Spark, as well as data governance and enterprise architecture principles, is highly desirable.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT frameworks supporting enterprise data and analytics workloads.
- Build and optimize data solutions using Snowflake, including data modeling, transformation, performance optimization, and workload management.
- Develop reusable and production-grade data engineering components using Python.
- Design and orchestrate complex workflows using Apache Airflow or similar orchestration platforms.
- Develop and support cloud-based data solutions using Microsoft Azure or comparable cloud technologies.
- Partner with business, analytics, architecture, governance, and technology teams to translate requirements into scalable technical solutions.
- Define technical designs, integration patterns, engineering standards, and best practices for enterprise data solutions.
- Implement appropriate data quality, monitoring, lineage, security, and operational controls across data pipelines.
- Troubleshoot production issues and drive improvements around performance, resiliency, scalability, and maintainability.
- Conduct design and code reviews and provide technical guidance to data engineering teams.
- Contribute to modernization of the data platform and adoption of modern engineering practices and technologies.
- Working experience in an Agile environment.
Required Qualifications
- 7+ years of professional experience in data engineering, data platforms, or related technology roles.
- Strong hands-on expertise with Snowflake & Star Schema Architecture.
- Advanced programming experience with Python & SQL.
- Strong experience with Apache Airflow or comparable workflow orchestration technologies.
- Hands-on experience with Microsoft Azure or another major cloud platform such as AWS or GCP.
- Strong experience designing and developing ETL/ELT pipelines, data integration solutions, and enterprise data processing workflows.
- Strong knowledge of SQL, data modeling, data warehousing, and performance optimization.
- Experience designing solutions for scalability, reliability, maintainability, and production support.
- Strong problem-solving, communication, and stakeholder-management skills.
- Ability to operate effectively in a complex enterprise environment and work across engineering, architecture, governance, and business teams.
Preferred Qualifications
- Experience with Databricks and Apache Spark.
- Experience with Azure Data Factory (ADF) and other Azure data services.
- Knowledge of data governance, metadata management, lineage, data quality, and access-control frameworks.
- Experience with enterprise data architecture and solution design.
- Understanding of modern architectural approaches such as lakehouse, medallion architecture, and cloud-native data platforms.
- Experience establishing engineering standards, reusable frameworks, and design patterns.
- Financial services or other highly regulated industry experience is a plus.
Ideal Candidate
The successful candidate combines strong hands-on data engineering capabilities with technical leadership. They should be comfortable moving between architecture and design discussions, hands-on engineering, technical problem-solving, and collaboration with business and technology stakeholders. The role is well suited for someone who can take ownership of complex data solutions from design through production while helping raise overall engineering standards across the team.
The expected base salary ranges from $112,000-$200,000. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, certifications and licenses obtained. Market and organizational factors are also considered. In addition to salary and a generous employee benefits package, including Medical, Dental and 401K plans, successful candidates are also eligible to receive a discretionary bonus.
Other Requirements
In office attendance is an essential function of this role. There is currently a requirement to be in the office a minimum 50% of the time, or five out of every 10 business days. Specific information about the requirements for your role will be communicated during the recruitment process.
Company Overview
Mizuho Financial Group, Inc. is the 15th largest bank in the world as measured by total assets of ~ $2 trillion. Mizuho's 60,000 employees worldwide offer comprehensive financial services to clients in 35 countries and 800 offices throughout the Americas, EMEA and Asia. Mizuho Americas is a leading provider of corporate and investment banking services to clients in the US, Canada, and Latin America. Through its acquisition of Greenhill, Mizuho provides M&A, restructuring and private capital advisory capabilities across Americas, Europe and Asia. Mizuho Americas employs approximately 3,500 professionals, and its capabilities span corporate and investment banking, capital markets, equity and fixed income sales & trading, derivatives, FX, custody and research.
We are an equal employment opportunity employer, and we comply with applicable laws prohibiting discrimination in all of the jurisdictions where we operate. AA Employer - M/F/Disability/Veteran. Accommodations are available upon request for applicants with disabilities and other covered reasons in accordance with applicable law. We participate in the E-Verify program. We maintain a drug-free workplace and reserve the right to require pre- and post-hire drug testing, as permitted by applicable law.
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Senior Level Data Lead Jobs: Frequently Asked Questions
How do I get a senior level data lead job?
Employers at this level want candidates who have owned end-to-end data initiatives, not just contributed to them. Demonstrating that you have set data strategy, governed data quality at scale, and mentored junior analysts gives you a clear edge. A portfolio of measurable business outcomes, combined with fluency in modern data stack tools and stakeholder communication, is what separates senior candidates from mid-level ones.
Which companies hire senior level data leads?
Companies hiring senior level data leads right now include Rippling, Oracle, and JPMorganChase, based on current listings on Migrate Mate as of November 2026. At this level, hiring tends to come from organizations with mature data functions that need experienced professionals to lead teams, define standards, and drive strategic data initiatives.
Are there remote senior level data lead jobs?
Yes, remote and hybrid opportunities are well represented at this level. About 39% of senior level data lead openings are remote or hybrid as of November 2026, reflecting how many organizations have normalized distributed leadership for senior data roles. Searching Migrate Mate by location preference lets you filter to fully remote or hybrid openings quickly.
What makes a data lead role senior level?
Senior level data lead roles are defined by ownership and scope rather than just technical skill. You are expected to set the direction for data architecture or analytics programs, make decisions that affect multiple teams or business units, and mentor less experienced data professionals. The difference from a mid-level role is accountability for outcomes, not just delivery of assigned work.
Which industries hire the most senior level data leads?
Senior Level data lead roles concentrate in Technology & Software, Banking & Financial Services, and Investment & Asset Management, based on current listings on Migrate Mate as of November 2026. These sectors tend to generate large, complex data environments where experienced leadership is needed to maintain quality, drive insights, and align data capabilities with business strategy.