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 in a remote environment
  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.

Hybrid 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