Data Analytics Lead Jobs
Data analytics lead jobs are open across finance, healthcare, retail, and technology, from mid-level analyst to senior lead and director, with specializations in business intelligence, data engineering, and predictive modeling. Find a role that fits from the openings below and apply directly.
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Showing 5 of 1,435+ Data Analytics Lead jobs
- Advises the Product Solutions teams on solutioning and adopting new and existing client-facing products and capabilities while crafting complex solutions and assessing risk to enhance the customer experience
- Leverages extensive knowledge of a cluster of products and capabilities to manage the strategic development of end-to-end product solution strategies and processes
- Partners with Sales to advise on strategic pricing for deals, contributes to the development of sales training and collateral, and oversees Request for Proposal (RFP) responses
- Manages the collection of client feedback and oversees the delivery of feedback to Product teams
- Drives the development of strategy and roadmaps for data governance initiatives, including next-generation data governance tooling and AI-for-data capabilities
- Collaborates with stakeholders, subject matter experts, and engineers to understand use cases, requirements, and dependencies, critically assessing proposed solutions.
- Communicates complex ideas effectively to collaborators and senior leaders using precise terminology and relatable examples
- Balances timeliness with quality under tight deadlines, managing multiple priorities and cross-functional partnerships.
- Ensures end-to-end relevance to stakeholder needs, from gathering business requirements and working with technology teams to achieve successful delivery
- Defines and refines customer-centric solution approaches that connect data governance capabilities to measurable business outcomes.
- Partners with business, technology, and control stakeholders to deploy solutions into production effectively and responsibly
- 8+ years of experience or equivalent expertise leading and developing solutions across multiple teams and a cluster of products
- Extensive experience facilitating sales cycle activities and developing and optimizing strategies and processes
- Demonstrable experience structuring and handling complex solutions for business problems to meet clients' needs
- Understanding and hands-on experience building agentic AI systems within regulated or compliance-driven environments
- 8+ years of experience developing enterprise-wide data, data governance, or AI strategy for large, complex organizations.
- 8+ years of experience either as a product manager, product designer, engineer, data analyst, data scientist, or user researcher
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
- Curious, hardworking, and detail-oriented, and motivated by complex analytical problems.
- Ability to collaborate effectively with stakeholders, subject matter experts, and engineers to translate needs into clear requirements
- Ability to balance quality and speed under tight deadlines while managing multiple priorities and partnerships.
- Ability to drive end-to-end delivery—from business requirements through implementation—ensuring outcomes meet stakeholder needs
- Direct experience with MCP (Model Context Protocol) designing tool schemas, building MCP servers, managing tool surface exposure, or integrating MCP into an agent platform
- Experience in regulated industries (financial services, healthcare, or government) with practical exposure to model risk management, audit trails, and compliance-driven engineering constraints.
- Familiarity with agent security concerns: prompt injection, tool misuse, over-privileged tool access, and blast radius containment strategies
- Experience building evaluation frameworks for LLM-based systems, including production-grade evaluation pipelines with structured outputs and regression tracking.
- Exposure to cloud-native AI infrastructure (managed model endpoints, model gateways, token/cost observability, and multi-tenant serving considerations)
- Experience contributing to developer-facing SDK or platform tooling (designing APIs, writing effective documentation, iterating based on adoption signals).
- Familiarity with responsible AI practices as they apply to agents, including human oversight requirements, escalation paths, intervention hooks, and auditability standards
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
- Advises the Product Solutions teams on solutioning and adopting new and existing client-facing products and capabilities while crafting complex solutions and assessing risk to enhance the customer experience
- Leverages extensive knowledge of a cluster of products and capabilities to manage the strategic development of end-to-end product solution strategies and processes
- Partners with Sales to advise on strategic pricing for deals, contributes to the development of sales training and collateral, and oversees Request for Proposal (RFP) responses
- Manages the collection of client feedback and oversees the delivery of feedback to Product teams
- Drives the development of strategy and roadmaps for data governance initiatives, including next-generation data governance tooling and AI-for-data capabilities
- Collaborates with stakeholders, subject matter experts, and engineers to understand use cases, requirements, and dependencies, critically assessing proposed solutions.
- Communicates complex ideas effectively to collaborators and senior leaders using precise terminology and relatable examples
- Balances timeliness with quality under tight deadlines, managing multiple priorities and cross-functional partnerships.
- Ensures end-to-end relevance to stakeholder needs, from gathering business requirements and working with technology teams to achieve successful delivery
- Defines and refines customer-centric solution approaches that connect data governance capabilities to measurable business outcomes.
- Partners with business, technology, and control stakeholders to deploy solutions into production effectively and responsibly
- 8+ years of experience or equivalent expertise leading and developing solutions across multiple teams and a cluster of products
- Extensive experience facilitating sales cycle activities and developing and optimizing strategies and processes
- Demonstrable experience structuring and handling complex solutions for business problems to meet clients' needs
- Understanding and hands-on experience building agentic AI systems within regulated or compliance-driven environments
- 8+ years of experience developing enterprise-wide data, data governance, or AI strategy for large, complex organizations.
- 8+ years of experience either as a product manager, product designer, engineer, data analyst, data scientist, or user researcher
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
- Curious, hardworking, and detail-oriented, and motivated by complex analytical problems.
- Ability to collaborate effectively with stakeholders, subject matter experts, and engineers to translate needs into clear requirements
- Ability to balance quality and speed under tight deadlines while managing multiple priorities and partnerships.
- Ability to drive end-to-end delivery—from business requirements through implementation—ensuring outcomes meet stakeholder needs
- Direct experience with MCP (Model Context Protocol) designing tool schemas, building MCP servers, managing tool surface exposure, or integrating MCP into an agent platform
- Experience in regulated industries (financial services, healthcare, or government) with practical exposure to model risk management, audit trails, and compliance-driven engineering constraints.
- Familiarity with agent security concerns: prompt injection, tool misuse, over-privileged tool access, and blast radius containment strategies
- Experience building evaluation frameworks for LLM-based systems, including production-grade evaluation pipelines with structured outputs and regression tracking.
- Exposure to cloud-native AI infrastructure (managed model endpoints, model gateways, token/cost observability, and multi-tenant serving considerations)
- Experience contributing to developer-facing SDK or platform tooling (designing APIs, writing effective documentation, iterating based on adoption signals).
- Familiarity with responsible AI practices as they apply to agents, including human oversight requirements, escalation paths, intervention hooks, and auditability standards
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Data Analytics Lead Jobs by Experience Level
Top Cities Hiring Data Analytics Leads
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Find Data Analytics Lead JobsData Analytics Lead Job Market
Who's Hiring
- Ryder System79
- CoStar26
- JPMorganChase26
- Capital One22
- American Express22
Top Industries Hiring
- Technology & Software19
- Insurance6
- Energy4
- Retail3
- Education3
What Employers Look For
The qualifications that appear most often in data analytics lead jobs.
- 5+ years of experience in data analytics or business intelligence roles
- Advanced proficiency in SQL and at least one scripting language such as Python or R
- Experience with BI tools such as Tableau, Looker, or Power BI
- Demonstrated ability to lead or mentor a team of analysts
- Bachelor's degree in statistics, computer science, mathematics, or a related field
- Experience with cloud data platforms such as Snowflake, BigQuery, or Redshift
Tips for Your Data Analytics Lead Job Search
Quantify impact on your resume
Data analytics lead roles expect measurable outcomes, not just responsibilities. Replace vague bullets with results: how much your models reduced churn, improved forecast accuracy, or cut reporting time. Hiring managers scan for numbers that prove your work moved a business metric.
Show your cross-functional leadership experience
Lead-level analytics roles are evaluated as much on stakeholder management as on technical skill. Highlight projects where you translated data findings for non-technical audiences, influenced product or finance decisions, or mentored junior analysts. That distinction separates lead candidates from senior individual contributors.
Target openings by your tool stack first
Filter your job search by the tools you know deepest, whether that's SQL, Python, dbt, Looker, Tableau, or Spark. Leads hired into a mismatched stack spend months catching up instead of delivering. Matching on tooling shortens your ramp and strengthens your interview answers.
Apply early to roles that fit
Migrate Mate lists data analytics lead openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a technical case for your interview
Data analytics lead interviews often include a take-home or live case study requiring you to scope an analytics problem, choose a methodology, and present findings. Practice walking through your reasoning out loud, not just your code. Interviewers are evaluating how you frame ambiguity, not just whether your query runs.
Negotiate scope, not just compensation
When you reach the offer stage, clarify team size, data infrastructure maturity, and whether the role has budget authority before accepting. A lead title at a company with no data engineering support can mean rebuilding pipelines solo rather than leading strategy, which affects your growth trajectory significantly.
Data Analytics Lead Jobs: Frequently Asked Questions
Which companies are hiring the most data analytics leads?
The companies hiring the most data analytics leads right now include Ryder System, CoStar, and JPMorganChase, with the largest share of openings in California, New York, and Virginia, based on current listings on Migrate Mate as of September 2026. Demand is consistently high in financial services, healthcare systems, and large technology companies that operate data-driven product teams.
How many data analytics lead jobs are remote?
About 74% of data analytics lead openings are fully remote or hybrid as of September 2026, reflecting sustained demand for distributed analytics leadership. Roles focused on self-service reporting, data strategy, and cross-functional stakeholder work tend to be the most remote-friendly, while positions that require close coordination with engineering or data infrastructure teams are more likely to require on-site presence.
How do you become a data analytics lead?
Start by building strong SQL and data visualization skills in an analyst or senior analyst role, then take on projects that involve stakeholder communication and mentoring. Seek out opportunities to own an analytics workstream end to end. Demonstrating that you can translate data into business decisions, not just produce reports, is what moves you from contributor to lead.
Can you get hired as a data analytics lead with limited leadership experience?
You can move into a data analytics lead role without a prior leadership title if you can show informal leadership in your portfolio. Highlight instances where you defined the analytics approach for a project, guided a junior colleague, or presented findings directly to a director or executive. Companies hiring their first analytics lead often prioritize technical depth and business judgment over a management title.
What does the data analytics lead interview process look like?
The process typically starts with a recruiter screen focused on your background and the team's goals, followed by a hiring manager conversation about your analytics approach and past impact. A technical round tests SQL, data modeling, or a case study where you diagnose a business problem using data. Final rounds often include a presentation to cross-functional stakeholders evaluating how you communicate findings and handle pushback on your conclusions.
Where can I find and apply to data analytics lead jobs?
You can find and apply to data analytics lead jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your experience and specialization, then apply directly to each one that fits.
See All 1,435+ Data Analytics Lead Jobs
Find roles that match your experience and apply in just a few clicks.
Find Data Analytics Lead Jobs