Mid Level Data Strategy Lead Jobs
Mid level data strategy lead jobs go to professionals ready to own end-to-end data initiatives, align cross-functional stakeholders, and translate analytical findings into strategic decisions with minimal oversight. Openings cover on-site, remote, and hybrid settings across Electronics & Hardware, Banking & Financial Services, and Technology & Software, with Apple, JPMorganChase, and Amazon Web Services hiring at this level now.
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Location: San Francisco, CA (Hybrid)
About the Opportunity
We are looking for a Strategic Project Manager on behalf of our client — a global technology company that provides large-scale data solutions to some of the world’s leading AI companies, retailers, brands, cybersecurity firms, and enterprise organizations.
Operating at the intersection of data and artificial intelligence, the company enables organizations to access, structure, and leverage massive amounts of publicly available web data to power AI models, business intelligence, market research, competitive analysis, and automation initiatives. Their technology supports data-driven decision-making for some of the fastest-growing and most innovative companies worldwide.
As the demand for high-quality data continues to accelerate, our client is expanding its Strategic Projects team and seeking an experienced Project Manager to lead complex, client-facing initiatives from planning through successful delivery.
Responsibilities
- Manage full project lifecycles, including planning, execution, delivery, and post-launch activities.
- Develop project plans, define milestones, allocate resources, and ensure timely completion.
- Monitor project budgets, track expenses, and report on financial performance.
- Communicate project progress, risks, and outcomes to internal and external stakeholders.
- Coordinate cross-functional teams, vendors, and partners to ensure successful project delivery.
- Identify and mitigate project risks while maintaining quality standards.
- Build strong client relationships and act as a trusted advisor throughout project execution.
- Ensure alignment between project goals and broader business objectives.
Requirements
- 5+ years of experience managing complex projects within a technology company, consulting firm, or professional services environment.
- Strong knowledge of project management methodologies, reporting practices, and performance metrics.
- Ability to understand business processes and translate requirements into actionable project plans.
- Excellent stakeholder management and communication skills.
- Basic technical understanding of data analysis, SQL, cloud technologies, IT infrastructure, and software development.
- Proven ability to manage multiple projects and priorities simultaneously.
Nice to Have
- Experience with business intelligence (BI) tools and analytics platforms.
- Exposure to data products, AI-related initiatives, or large-scale data operations.
- Experience working with e-commerce, retail, consumer brands, or digital commerce organizations.
- Background in client-facing consulting, professional services, or managed services environments.
What You’ll Get
- The opportunity to work on high-impact projects supporting leading AI and technology companies.
- Exposure to cutting-edge data and artificial intelligence initiatives.
- A collaborative, fast-paced environment with significant ownership and visibility.
- The chance to work with global clients and multidisciplinary teams solving complex business challenges.
Pay: $130,000.00 - $185,000.00 per year
Benefits:
- 401(k)
- Health insurance
- Paid time off
Work Location: Hybrid remote in San Francisco, CA 94107
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Who's Hiring



Top Industries Hiring
- Electronics & Hardware
- Banking & Financial Services
- Technology & Software
- Distribution & Wholesale
- Fintech
Mid Level Data Strategy Lead Jobs: Frequently Asked Questions
How do I get a mid level data strategy lead job?
Position yourself around ownership and impact: highlight projects where you led the data strategy from framing the problem through to delivering recommendations, not just executing tasks. Emphasize cross-functional work, stakeholder communication, and any moments where your analysis shaped a business decision. A portfolio of documented outcomes, even from a single employer, signals mid level readiness far more than tenure alone.
Which companies hire mid level data strategy leads?
Companies hiring mid level data strategy leads right now include Apple, JPMorganChase, and Amazon Web Services, based on current listings on Migrate Mate as of July 2026. Hiring at this level tends to come from organizations with established data functions that need strategists who can execute independently, including large enterprises building out analytics practices and growth-stage companies formalizing their data operations.
Are there remote mid level data strategy lead jobs?
Yes, remote and hybrid options are common at this level. About 67% of mid level data strategy lead openings are remote or hybrid as of July 2026, reflecting how data strategy work translates well to distributed collaboration. Fully on-site roles tend to cluster at organizations where the data strategy lead works closely with executive stakeholders or embedded operations teams.
How do I move up to a mid level data strategy lead role?
Growth into a mid level data strategy lead role comes from deliberately expanding your scope over time: seek out projects where you own the problem definition, not just the analysis. Build fluency in translating data findings into business recommendations, accumulate experience working with non-technical stakeholders, and document the measurable outcomes of your work. Demonstrating strategic judgment, not just technical skill, is what closes the gap from junior to mid level.
Which industries hire the most mid level data strategy leads?
Mid Level data strategy lead roles concentrate in Electronics & Hardware, Banking & Financial Services, and Technology & Software, based on current listings on Migrate Mate as of July 2026. These sectors tend to drive hiring at this level because they have mature data infrastructures, competitive pressure to monetize insights, and enough organizational scale to support dedicated strategy roles distinct from pure data engineering or analytics execution.