About the roleWe are looking for a data engineer who thrives at the intersection of messy data and meaningful insight. You'll work across large, complex data lake and warehouse environments, bringing disparate datasets together to answer the questions our business actually cares about.This is an end-to-end role. You'll partner with product managers, BI developers, operations leaders, and fellow engineers to design solutions, then own them through to production. If you are analytical, self-directed, and energized by turning raw data into something people can act on, you will fit in well here.What you will doPartner with project managers, business stakeholders, data architects, and modelers to translate requirements into working solutionsDesign, build, and maintain scalable data platforms (lakes, warehouses, Lakehouse's, and streaming systems) with a focus on clean modeling, sound schema design, and reliable access across the organizationBuild batch and streaming pipelines that are observable, tested, and cost-awareStay curious about the data landscape. Evaluate new and existing tools, and make thoughtful calls about what belongs in our architectureChampion best practices in data processing, reporting, and analysis: integrity, testing, lineage, validation, and documentation that actually gets readWhat we are looking forBachelor's degree in Computer Science or a related technical field, or equivalent experience5+ years in ETL/ELT, data modeling, and data architecture, with strong SQL and Python and hands-on work with large datasets and warehousing2+ years on AWS or Azure (e.g., Redshift, RDS, S3, EMR on AWS, or ADF, ADLS, Synapse on Azure)Strong command of Apache Spark (or similar) for designing, coding, and tuning big data processesHands-on experience with modern data platforms like Databricks or Microsoft Fabric, and with tools like dbt, Airflow, or Delta/Iceberg, is a plusA track record of handling data well: lineage, quality, observability, and discoverabilitySolid grasp of distributed systems, including batch and stream pipelines, partitioning, and MPP optimizationComfort across the full SDLC: coding standards, code review, Git, CI/CD, and testing
Job Title
Data Engineer