Data Strategy Lead Jobs
Data Strategy Lead jobs are open across financial services, healthcare, technology, and retail, from senior analyst to director level, with specializations in data governance, analytics strategy, and enterprise data architecture. Find a role that fits from the openings below and apply directly.
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At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Join Apple, and help us leave the world better than we found it. Apple’s Strategic Data Solutions (SDS) team is responsible for mitigating fraud, waste and abuse company-wide while optimizing and empowering our customers and internal partners.
The SDS software engineering team is building an environment to enable ground breaking data analysis over Petabytes of data. We work side-by-side with machine learning engineers and implement scalable, easy-to-use systems and tools. We are seeking a customer- focused, passionate and driven Software Engineer with experience in building analytic tools and solutions.
Description
With the expansive data we have, our job is to build meaningful data relationships and engagement experiences for our internal customers. If you’re interested in being a part of a team that’s constantly learning and problem-solving, we’d love to talk with you. As a Software Engineer on the SDS team, you will work closely with Machine Learning Engineers and other Software Engineers to lead the design and implementation of systems and tools to support the ML initiatives for Apple Retail and Fraud prevention efforts of SDS.
You will be:
- Developing and implementing production software for retail ML initiatives and preventing retail fraud
- Responsible for system architecture design
- Working with external infrastructure teams to drive the development of infrastructure needs
- Innovating by recognizing opportunities for automation and tools improvements
- Responsible for developing and implementing process improvements to bring efficiency and stability to fraud analytics
- Responsible for technical leadership for a team of data scientists
- Responsible for Release engineering and ML Operations
- Expected to operate independent of supervision, with limited guidance
- Lead the team to increase the level of maturity and skill in analytical software development
Preferred Qualifications
Experience with Docker, Kubernetes, or cloud platform deployment
Experience with Relational databases and NoSQL databases
Demonstrated understanding of the full software development lifecycle
Excellent problem solving, critical thinking, and communication skills
Solid grasp of computer science fundamentals including data structures and algorithms
Solid ability to evaluate and apply new technologies in a short time
Self-motivated, proactive, and solution-oriented
Minimum Qualifications
BS or advanced degree in Computer Science, related field or equivalent experience
Mastery of one of Java, Python, or equivalent language
Experience with Big Data & building ETL Data Pipelines
Experience with messaging systems, such as Kafka
8+ years of experience in software engineering/data science
Experience building data science or data analysis tools on AWS/GCP/Cloud based systems
At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Join Apple, and help us leave the world better than we found it. Apple’s Strategic Data Solutions (SDS) team is responsible for mitigating fraud, waste and abuse company-wide while optimizing and empowering our customers and internal partners.
The SDS software engineering team is building an environment to enable ground breaking data analysis over Petabytes of data. We work side-by-side with machine learning engineers and implement scalable, easy-to-use systems and tools. We are seeking a customer- focused, passionate and driven Software Engineer with experience in building analytic tools and solutions.
Description
With the expansive data we have, our job is to build meaningful data relationships and engagement experiences for our internal customers. If you’re interested in being a part of a team that’s constantly learning and problem-solving, we’d love to talk with you. As a Software Engineer on the SDS team, you will work closely with Machine Learning Engineers and other Software Engineers to lead the design and implementation of systems and tools to support the ML initiatives for Apple Retail and Fraud prevention efforts of SDS.
You will be:
- Developing and implementing production software for retail ML initiatives and preventing retail fraud
- Responsible for system architecture design
- Working with external infrastructure teams to drive the development of infrastructure needs
- Innovating by recognizing opportunities for automation and tools improvements
- Responsible for developing and implementing process improvements to bring efficiency and stability to fraud analytics
- Responsible for technical leadership for a team of data scientists
- Responsible for Release engineering and ML Operations
- Expected to operate independent of supervision, with limited guidance
- Lead the team to increase the level of maturity and skill in analytical software development
Preferred Qualifications
Experience with Docker, Kubernetes, or cloud platform deployment
Experience with Relational databases and NoSQL databases
Demonstrated understanding of the full software development lifecycle
Excellent problem solving, critical thinking, and communication skills
Solid grasp of computer science fundamentals including data structures and algorithms
Solid ability to evaluate and apply new technologies in a short time
Self-motivated, proactive, and solution-oriented
Minimum Qualifications
BS or advanced degree in Computer Science, related field or equivalent experience
Mastery of one of Java, Python, or equivalent language
Experience with Big Data & building ETL Data Pipelines
Experience with messaging systems, such as Kafka
8+ years of experience in software engineering/data science
Experience building data science or data analysis tools on AWS/GCP/Cloud based systems
Data Strategy Lead Jobs by Experience Level
Top Cities Hiring Data Strategy Leads
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Find Data Strategy Lead JobsData Strategy Lead Job Market
Who's Hiring
- Meta24
- JPMorganChase16
- Apple10
- Google7
- Capital One7
Top Industries Hiring
- Technology & Software26
- Banking & Financial Services9
- Consulting & Professional Services9
- Electronics & Hardware6
- Retail5
What Employers Look For
The qualifications that appear most often in data strategy lead jobs.
- 5+ years of experience in data strategy, analytics, or enterprise data management
- Proficiency with cloud data platforms such as Snowflake, BigQuery, or Databricks
- Experience developing and implementing data governance frameworks and policies
- Strong stakeholder management and executive communication skills
- Familiarity with data modeling concepts, metadata management, and data cataloging tools
- Bachelor's or master's degree in a quantitative, computer science, or business field
Tips for Your Data Strategy Lead Job Search
Quantify your data strategy impact
Hiring managers for data strategy leads expect concrete outcomes, not process descriptions. Reframe your resume bullets around decisions your strategy informed, cost reductions from data consolidation, or adoption rates of new data standards across business units.
Tailor your resume to the data maturity level
A company building its first data warehouse needs a different lead than one optimizing a mature lakehouse. Read the job description for signals like 'establish frameworks' versus 'scale existing infrastructure' and mirror that language in your summary and experience sections.
Highlight cross-functional stakeholder experience
Data strategy leads are evaluated heavily on their ability to align engineering, product, and executive teams. Name the specific stakeholder groups you've worked with and the business outcomes those partnerships produced, not just the technical deliverables.
Apply early to roles that fit
Migrate Mate lists data strategy 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 data strategy case study for interviews
Most data strategy lead interviews include a structured exercise where you diagnose a fictional company's data problems and propose a roadmap. Practice framing your answer around business value first, then tooling and architecture, so your reasoning reflects a lead's perspective rather than an analyst's.
Negotiate scope, not just compensation
When you receive an offer, clarify reporting structure, budget authority, and whether the role owns the data roadmap or advises on it. Ambiguity in those areas predicts friction after you start, and asking directly signals strategic maturity to the hiring team.
Data Strategy Lead Jobs: Frequently Asked Questions
Which companies are hiring the most data strategy leads?
The companies hiring the most data strategy leads right now include Meta, JPMorganChase, and Apple, with the largest share of openings in New York, California, and Texas, based on current listings on Migrate Mate as of August 2026. Demand is strongest at large financial institutions, health systems, and enterprise technology companies undertaking major data modernization initiatives.
How many data strategy lead jobs are remote?
About 73% of data strategy lead openings are fully remote or hybrid as of August 2026, making it one of the more location-flexible senior roles in data. Sub-specializations focused on roadmap development, governance policy, and vendor evaluation tend to be the most remote-friendly, while roles tied to hands-on platform migration or embedded business-unit partnerships more often require some on-site presence.
How do you become a data strategy lead?
Most data strategy leads start in analytics, data engineering, or business intelligence before moving into roles with strategic scope. Building expertise in data governance and stakeholder alignment is essential. Taking ownership of a cross-functional data initiative, earning a relevant certification in cloud data platforms or data management, and demonstrating measurable business outcomes from your work are the clearest steps toward a lead-level role.
Can I get a data strategy lead job with limited experience?
Moving into a data strategy lead role with limited experience is achievable if you can demonstrate strategic thinking alongside technical credibility. Focus on roles at smaller companies or startups where the scope is broader and the title reflects potential as much as tenure. Contributing to a data governance project, leading a data quality initiative, or presenting a data roadmap to leadership in a current role builds the portfolio that lead-level hiring managers look for.
What does the data strategy lead interview process look like?
The process typically begins with a recruiter screen focused on background and role fit, followed by a hiring manager conversation about your approach to data strategy and stakeholder alignment. Later rounds usually include a case study or take-home exercise where you diagnose a data challenge and propose a roadmap, plus panel interviews with engineering leads, product managers, or executives whose teams you would support.
Where can I find and apply to data strategy lead jobs?
You can find and apply to data strategy lead jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background and apply directly to each one that fits.
See All 296+ Data Strategy Lead Jobs
Find roles that match your experience and apply in just a few clicks.
Find Data Strategy Lead Jobs