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Tier-1 brand, mid-level data engineer in metro with broad required skillset increases competition.
Core data engineering skills (ETL, Databricks, S3, Kubernetes) transfer easily across industries.
Explicit 2-5 years plus multiple mandatory platform and tooling requirements increases shortlist rigidity.
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Develop and optimize data structures and pipelines to support advanced analytics, machine learning, and reporting needs.
Maintain data warehouses and lakes on platforms including Kubernetes, Teradata, and Databricks with appropriate storage solutions on-prem and cloud.
Collaborate with partners to ensure data quality, process optimization, handle migrations, and enforce data governance compliance.
Bachelor's Degree preferred; combinations of coursework and professional experience may be considered.
2-5 years of relevant work experience in data engineering or related fields.
Experience with data storage and processing platforms such as Kubernetes, Teradata, Databricks, AWS S3, and Redshift.
Ability to work nights and weekends with a variable schedule as necessary.
Experienced in designing and managing data pipelines and storage across both on-premises and cloud environments.
Skilled in troubleshooting data lineage and ensuring data quality throughout ingestion and processing phases.
Comfortable working with cross-functional technology partners to optimize data sourcing and governance in regulated environments.