Lead Data Engineer
Logicbroker is an Agentic Commerce Orchestration Engine helping enterprise retailers, brands, suppliers, and distributors connect and grow. The company is seeking a Lead Data Engineer to drive analytics and data platform delivery by translating engineering specifications into agile work, leading a small contractor team, and implementing complex data transformations and models. The role focuses on Databricks-based Medallion architecture, data warehouse unification, pipeline reliability, and proactive stakeholder communication.
Responsibilities
- 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
Skills
- 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
- 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
Benefits
- Hybrid flexibility: remote or in-office work with autonomy and accountability
- Leadership invested in employee growth and open to employee ideas
- Team offsites and Slack shoutouts to celebrate progress and recognize contributions
Company Overview