Our hiring partner is the orchestration engine behind modern digital commerce, helping enterprise retailers, brands, suppliers, and distributors connect and grow. Their intelligent commerce network powers billions in GMV for global leaders, automating the entire process from discovery to doorstep and stock to dock. By making products discoverable, shoppable, fulfillable, and returnable, they enable clients to grow faster, delight customers, and run smarter operations.

This is a mission-driven organization transforming digital commerce through innovation and agility. The engineering team has been an early adopter of AI-driven development, building its own AI implementations and integrating emerging technologies into everyday workflows. They foster a collaborative, no-ego environment where the best ideas win, autonomy and accountability are trusted, and leadership is genuinely invested in employee growth.

Why This is a High-Impact Opportunity

1. Lead Delivery on a Critical Initiative: Drive execution of an approved Data Warehouse Unification Plan, translating specifications into agile workloads and delivering high-quality progress.
2. Player-Coach Leadership: Lead a small delivery team while remaining hands-on, owning the most complex data transformations and modeling work.
3. Shape the Future of Analytics: Continue building and refining analytics foundations driven by Gold-layer data models, ensuring outputs are performant and consumable by external analytics engines.
4. AI-Driven Innovation: Join a team that embraces AI-assisted development, drives engineering efficiency, and continuously innovates at scale.

About the Role

We are seeking a Lead Data Engineer to drive delivery across analytics and data platform initiatives. This role is a hands-on technical lead responsible for translating well-defined engineering specifications into executable work, coordinating a small team of contractors, and ensuring consistent, high-quality progress.

You will partner closely with an Engineering Manager who owns architectural direction and high-level specifications. Your focus will be execution leadership: refining specifications into agile workloads, assigning work effectively, contributing directly to complex implementations, and clearly communicating progress, risks, and areas requiring clarification.

Key Responsibilities

1. Lead a small delivery team and act as a player-coach by owning the most complex data transformations and modeling work, while reviewing and guiding contractor contributions.
2. Keep work unblocked, well-scoped, and on track to ensure consistent delivery momentum.
3. Continue building and refining analytics foundations driven by Gold-layer data models.
4. Design and implement Medallion architecture transformations (Bronze → Silver → Gold).
5. Ensure Gold-layer outputs are well-modeled, performant, and consistently consumable by an external analytics engine.
6. Improve the reliability, clarity, and maintainability of existing pipelines.
7. Partner with the Engineering Manager to execute an approved Data Warehouse Unification Plan RFC.
8. Plan and deliver sprint-based execution, with execution as the primary focus given the RFC is already defined.
9. Work across multiple Databricks instances as part of a GDPR-first data strategy.
10. Surface execution risks, sequencing concerns, and dependencies early to support successful delivery.
11. Translate engineering specifications into clear, scoped tickets, logical sprint plans, and well-sequenced workstreams.
12. Assign work appropriately across contractors based on skill level and complexity.
13. Implement complex Spark and Databricks transformations directly as needed.
14. Review pull requests and uphold quality standards across all delivered work.
15. Communicate progress, blockers, and clarity needs clearly and proactively with stakeholders.
16. Maintain delivery momentum without unnecessary process overhead.

Required Qualifications

1. Strong hands-on experience with Databricks, PySpark, and Spark SQL.
2. Proven experience implementing Medallion architecture.
3. Solid data modeling skills, especially for analytics and reporting use cases.
4. Experience leading delivery for small engineering teams (formal management not required).
5. Comfort working with partially defined requirements and refining them collaboratively.
6. Clear written and verbal communication skills.
7. Must be legally authorized to work in the United States. Visa sponsorship is not available.

Preferred Qualifications

1. Experience supporting GDPR-compliant data strategies.
2. Exposure to multi-region or multi-tenant data platforms.
3. Familiarity with external analytics tools consuming warehouse data.
4. Familiarity with various data flows, with sources in Azure, AWS, GCP, and others.

Apply Now

If you are a hands-on data engineering leader with deep expertise in Databricks, Spark, and Medallion architecture, and you are excited by the challenge of driving delivery on a critical analytics platform initiative, we encourage you to apply. This is a defining opportunity to lead execution and shape the future of a data-driven commerce platform.