Data Analyst Lead Jobs
Data Analyst Lead jobs are open across finance, healthcare, retail, and technology, at every level from mid-senior to principal, with specializations in business intelligence, predictive modeling, and data governance. Find a role that fits from the openings below and apply directly.
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Showing 5 of 1,434+ Data Analyst 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 Analyst Lead Jobs by Experience Level
Top Cities Hiring Data Analyst Leads
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Find Data Analyst Lead JobsData Analyst 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 analyst lead jobs.
- 5 or more years of experience in data analytics with at least 2 years in a lead or senior capacity
- Advanced proficiency in SQL and at least one scripting language such as Python or R
- Experience with BI platforms such as Tableau, Power BI, or Looker for dashboard development and reporting
- Bachelor's degree in statistics, mathematics, computer science, economics, or a related quantitative field
- Demonstrated ability to translate business questions into analytical frameworks and communicate findings to non-technical stakeholders
- Familiarity with cloud data platforms such as Snowflake, BigQuery, or Redshift and experience with large-scale datasets
Tips for Your Data Analyst Lead Job Search
Quantify your team leadership impact
Hiring managers for lead roles want to see that you've directed analysts, not just done the work yourself. List the number of direct reports you managed and specific outcomes your team delivered, like reduced reporting cycle time or improved model accuracy.
Tailor your portfolio to the industry
A data analyst lead portfolio that works for a fintech role won't land the same way at a healthcare company. Swap in case studies that mirror the domain, whether that's claims data, transaction fraud, or customer churn, so reviewers see immediate relevance.
Filter openings by stack, not just title
Data analyst lead postings vary enormously by required tools. Search by SQL dialect, BI platform, or cloud environment alongside the job title to surface roles where your existing skills are a direct match and skip the ones that need a full ramp.
Apply early to roles that fit
Migrate Mate lists data analyst 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 stakeholder communication example
Lead-level interviews almost always include a scenario about translating complex findings for non-technical executives. Have a specific story ready where you simplified an analysis, drove a decision, and can articulate what changed as a result of your recommendation.
Negotiate scope before you negotiate pay
At the lead level, role definition matters as much as compensation. Before accepting, confirm whether you'll own the analytics roadmap, have budget authority, or are stepping into a player-coach versus a pure management position, since title alone doesn't answer that.
Data Analyst Lead Jobs: Frequently Asked Questions
Which companies are hiring the most data analyst leads?
The companies hiring the most data analyst 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 strong in financial services, healthcare systems, and large consumer technology companies.
How many data analyst lead jobs are remote?
About 74% of data analyst lead openings are fully remote or hybrid as of September 2026, making it one of the more flexible senior individual-contributor and people-manager roles in the data field. Business intelligence, marketing analytics, and product analytics sub-specialties tend to have the highest share of remote-eligible postings.
How do you become a data analyst lead?
Start by building deep proficiency in SQL, a scripting language like Python, and at least one BI platform. Progress from analyst to senior analyst by taking ownership of end-to-end projects rather than task-level work. Develop stakeholder communication skills by presenting findings directly to business owners. Volunteer to mentor junior analysts or coordinate cross-functional data requests, since demonstrated leadership is what hiring managers look for when promoting or hiring into a lead title.
Can you get a data analyst lead job without prior leadership experience?
Yes, some employers will hire a strong senior analyst into a lead role if you can show informal leadership, such as mentoring colleagues, owning a data product, or driving an analytics initiative from scoping through delivery. Frame your resume around decisions you influenced and projects where you set the analytical direction, not just tasks you completed. Smaller companies and high-growth startups tend to be more open to first-time leads than large enterprises.
What does the data analyst lead interview process look like?
Most processes run three to four rounds. An initial screen with a recruiter or hiring manager covers your background and leadership style. A technical round tests SQL, data modeling, or a take-home case study. A stakeholder or cross-functional round assesses how you communicate insights and prioritize competing requests. Final rounds often include a presentation to senior leadership where you walk through a past project and defend your methodology and business recommendations.
Where can I find and apply to data analyst lead jobs?
You can find and apply to data analyst lead jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your skills, experience level, and preferred industry, then apply directly to each listing from the same place.
See All 1,434+ Data Analyst Lead Jobs
Find roles that match your experience and apply in just a few clicks.
Find Data Analyst Lead Jobs