Tech Lead

About Elevate

Elevate is a full-service consulting firm specializing in brand consulting, sales strategy, data-driven insights, and talent optimization. Founded in 2018, Elevate supports sports teams and leagues in transforming their operations and driving performance. Today, Elevate operates globally with a team of 700+ employees in 20 locations, focusing on the convergence of media, entertainment, and consumer brands.

Where you come in

We are seeking a Tech Lead for data and insights products to lead the technical direction for our platform. This role requires strong backend engineering experience, broad data exposure, full-stack fluency, and hands-on coding ability. You will also lead a distributed engineering team, including in-house and agency partners, and partner with product and design teams to ensure clear scope and tradeoffs.

What You'll Bring

• 7+ years of professional software engineering experience, with at least 2 years in a technical leadership role.
• Strong backend engineering experience, including API design, service architecture, data flow design, and cloud-native systems.
• Broad data exposure, including SQL, analytics platforms, data modeling, validation, and debugging data quality issues.
• Full-stack fluency. You do not need to be primarily frontend, but you should be comfortable partnering on product UI decisions when the user experience depends on technical implementation.
• Experience building data-intensive applications where correctness, trust, performance, and user comprehension matter.
• Strong hands-on coding ability. You still enjoy writing production code, reviewing code, and leading by example.
• Ability to lead distributed and agency engineering teams without treating them as a black box. You can ask the right questions, challenge estimates, clarify scope, and keep delivery moving.
• Product engineering judgment. You understand that the goal is not just shipping tickets, it is solving business and customer problems.
• Clear communication with technical and non-technical stakeholders, including product, design, business leaders, and client-facing teams.
• Comfort partnering with ML engineers and building reliable product workflows around AI and ML outputs.

How You'll Make an Impact

• Lead technical direction for the data and insights platform, including backend services, APIs, data workflows, and AI-assisted product capabilities.
• Deliver hands-on features, especially where backend, data, and product experience overlap.
• Provide technical leadership for a distributed engineering team, including in-house engineers and agency partners.
• Clarify planning and delivery tradeoffs across product priorities, stakeholder needs, engineering capacity, and technical sustainability.
• Improve product trust, data quality, reliability, and usability.
• Partner with product and design so scope, acceptance criteria, and tradeoffs are clear before work enters development.
• Partner with the ML engineer to turn AI and ML work into production-quality product capabilities rather than isolated experiments.
• Partner with the full-stack engineer to connect frontend polish with backend feasibility and data constraints.
• Help leadership make better investment decisions by translating engineering work into business outcomes like internal adoption, external client growth, usage, trust, and operational efficiency.

Your Journey: First 90 Days

• Learn the product ecosystem, codebase, data flows, infrastructure, and current delivery process.
• Build relationships with in-house engineers, agency partners, product and design stakeholders, and business users.
• Start contributing code to understand the system from the inside.
• Identify the highest-risk technical and delivery gaps, especially around backend ownership, data trust, team coordination, and release predictability.

• Lead a meaningful data and insights feature or technical improvement from scope through delivery.
• Improve the development workflow with clearer estimates, acceptance criteria, PR expectations, and release visibility.
• Partner with the ML engineer on reliable product workflows around AI and ML capabilities.
• Help turn product priorities into a realistic roadmap with clear tradeoffs.

• Own technical planning for upcoming product platform work.
• Represent engineering in cross-functional planning and stakeholder conversations.
• Establish a repeatable delivery rhythm for the distributed engineering team.
• Identify where the platform needs deeper backend, data, frontend, or ML investment to hit business goals.

Why This Role Matters Now

This product area has major business potential, but it needs stronger technical ownership to move from useful capability to trusted, scalable product. This role brings the hands-on leadership needed to reduce ambiguity, strengthen delivery, improve product trust, and help the platform support both internal adoption and external client growth.

The Technology You'll Work With

• Python web frameworks such as FastAPI or Flask.
• AWS services such as Lambda, ECS, API Gateway, S3, Redshift, Glue, Aurora, or similar cloud and data infrastructure.
• Modern frontend technologies such as React and TypeScript.
• ETL or ELT workflows, analytics engineering, data warehousing, or business intelligence platforms.
• Customer data platforms, research tools, analytics SaaS products, or other data-heavy B2B products.
• Sports, entertainment, sponsorship, ticketing, or fan data experience.

Position and Benefits Details

• Full-time – Exempt
• Anticipated Base Salary: $100,000 - $185,000 (this position is bonus eligible)
• Medical, Dental, Vision, Life, Short-Term & Long-Term Disability Insurance + FSA, HSA, and more
• 401k Employer Match after meeting eligibility requirements
• 14 Paid Holidays
• Paid Parental Leave