Data Engineering Lead

Job description

We're looking for a Data Engineering Lead who will own our data platform end-to-end, from architecture decisions to hands-on implementation. You'll join a small, focused data team where your work directly shapes how we build. This is not a role where you'll wait for requirements to be handed to you. You'll work directly with Product, Analytics, and Engineering leadership to understand business problems and translate them into data solutions. **Responsibilities** - Make architectural decisions backed by data; you'll be asked, "why this approach? " and need to answer with scale requirements, cost analysis, and trade-offs. - Design and present technical solutions to leadership; anticipate questions and come prepared. - Proactively identify technical debt and systemic problems; don't wait to be asked. - Work directly with Product Managers to understand business needs and translate ambiguous requirements into concrete technical specs. - Lead requirements discussions; ask probing questions, propose interpretations, and confirm understanding. - Create clarity for the team and define problem statements; don't wait for them. - Set the standard through your own work, your code, designs, and documentation, which become the reference point. - Be generous with context, explain your thinking, share what you're learning, and unblock others. - Raise the bar by how you operate, not just what you deliver. **Requirements** - 6+ years of hands-on experience with cloud data platforms (AWS preferred: Glue, Redshift, Athena, EMR) and in-depth knowledge of real-time data architectures. - Strong SQL skills and experience with data modeling (dimensional modeling, star schemas, SCDs). - Experience with data quality frameworks, testing strategies, and observability. - Familiarity with modern data stacks (dbt, Airflow, Spark, or similar). - Experience setting up CI/CD for data pipelines. This job was posted by Abin Chandra from Loco.