Job Summary
We are hiring a Lead Data Engineer to drive delivery across our 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 intelligently, contributing directly to complex implementations, and clearly communicating progress, risks, and clarity needs.
What You'll Do:
- 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.
- Keep work unblocked, well-scoped, and on track to ensure consistent delivery of momentum.
- Continue building and refining analytics foundations driven by Gold-layer data models.
- Design and implement Medallion architecture transformations (Bronze → Silver → Gold).
- Ensure Gold-layer outputs are well-modeled, performant, and consistently consumable by an external analytics engine.
- Improve the reliability, clarity, and maintainability of existing pipelines.
- Partner with the Engineering Manager to execute an approved Data Warehouse Unification Plan RFC.
- Plan and deliver sprint-based execution, with execution as the primary focus given the RFC is already defined.
- Work across multiple Databricks instances as part of a GDPR-first data strategy.
- Surface execution risks, sequencing concerns, and dependencies early to support successful delivery.
- Translate engineering specifications into clear, scoped tickets, logical sprint plans, and well-sequenced workstreams.
- Assign work appropriately across contractors based on skill level and complexity.
- Implement complex Spark and Databricks transformations directly as needed.
- Review pull requests and uphold quality standards across all delivered work.
- Communicate progress, blockers, and clarity needs clearly and proactively with stakeholders.
- Maintain delivery momentum without unnecessary process overhead.
What We Need:
- Strong hands-on experience with Databricks, PySpark, and Spark SQL
- Proven experience implementing Medallion architecture
- Solid data modeling skills, especially for analytics and reporting use cases
- Experience leading delivery for small engineering teams (formal management not required)
- Comfort working with partially defined requirements and refining them collaboratively
- Clear written and verbal communication skills
Nice to Have: - Experience supporting GDPR-compliant data strategies
- Exposure to multi-region or multi-tenant data platforms
- Familiarity with external analytics tools consuming warehouse data
- Familiarity with various data flows, with sources in Azure, AWS, GCP, and others
Why Logicbroker:
Mission-Driven Culture: Be part of a company transforming digital commerce through innovation and agility—your work directly shapes how global brands connect with customers.
Collaborative, No-Ego Environment: We believe the best ideas win, not the loudest voices. You’ll work alongside teammates who challenge and support each other.
Flexibility with High-Performance Energy: Whether remote or in-office, we foster autonomy and accountability—because we trust you to own your success.
Leadership That Listens: Our executives are not just accessible—they’re invested in your growth, open to your ideas, and committed to building a company where people thrive.
Celebrated Wins, Shared Learnings: From team offsites to Slack shoutouts, we celebrate progress and learn from setbacks together