Lead Data Engineer

Senior individual contributor focused on designing, building, and hardening data pipelines in a modern Enterprise Data Lakehouse. Lead engineer will drive pipeline stability, performance, and data quality across the platform while operating autonomously and influencing platform standards.Key Responsibilities:Design, build, and optimize data pipelines that integrate diverse sources into a centralized LakehouseTroubleshoot, performance test, and stabilize production data pipelines supporting critical business use casesDesign and enforce data quality frameworks to ensure correctness, trust, and reliabilityTranslate business and operational requirements into scalable technical solutionsTune and optimize SQL performance, data models, partitioning, and compaction strategiesSupport and improve platform performance across ingestion, storage, and analytics layersCollaborate directly with business leaders, engineers, and operational teams to deliver data‑driven solutionsApply strong software engineering practices including testing, version control, CI/CD, and deployment standardsHelp establish technical patterns, standards, and best practices as the data platform evolvesMentor other data engineers through technical leadership and collaborationQualifications:5+ years experience as an AWS Data Engineer designing and supporting data pipelinesStrong Python and SQL experience, including SQL performance tuningExperience owning and supporting production data systemsSolid software engineering background (development, testing, version control, deployment)Experience implementing or working within a Data Lakehouse architectureStrong communication skills and comfort working with non-technical stakeholdersPreferred Skills:Hands‑on experience with Snowflake (or deep experience with comparable cloud data platforms)Experience with AWS and modern data tooling (e.g., Airflow, dbt, Airbyte)Familiarity with Kubernetes conceptsGeneral DevOps exposure and understanding of production deployment modelsPower BI experienceBackground in oil & gas or industrial data environments