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Metro location plus popular data role and broad lakehouse skillset produce moderate applicant competition.
Medium: transferable data engineering skills, but lakehouse governance and compliance increase domain specificity.
High: explicit 10+ years, 5+ years lakehouse leadership, and mandatory cloud/data tooling experience.
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Design, build, and operate scalable data lake and lakehouse architectures on AWS including S3, Glue, Lake Formation, Snowflake, and Delta Lake.
Develop and optimize batch and real-time data pipelines, ensuring secure, governed, and accessible data integration for analytics and AI products.
Lead data governance implementation, promote modern data engineering frameworks, mentor team members, and contribute to platform roadmaps.
10+ years in Data Engineering, Software Engineering, or Cloud Engineering with 5+ years leading data lakehouse transformations on AWS.
Bachelor’s degree in Computer Science, Data Science, or related field; Master’s preferred.
Strong experience with AWS data lake services (S3, Glue, Lake Formation), Snowflake, Delta Lake, data governance tools (Unity Catalog, Collibra, Atlan).
Proficiency in Python, SQL; pipeline orchestration tools (Airflow, Step Functions, dbt); and DevOps practices (Terraform/CloudFormation, CI/CD).
Experienced leader in cloud-based data lakehouse architecture and transformation initiatives, especially on AWS.
Technical expertise balancing hands-on development with governance, security, and DevOps automation for large-scale data platforms.
Able to collaborate across teams to translate business needs into governed, observable data products with strong stakeholder communication skills.