Data Management Engineer

About the Role

• Collaborate with data engineers and platform counterparts to align ingestion patterns with data management requirements. • Serve as the primary technical owner for the configuration, administration, and enhancement of the Alation data catalog. • Contribute documentation, reusable patterns, and best practices that improve consistency and shared ways of working. • Integrate metadata, ownership, and quality context into ingestion pipelines to reduce manual effort and rework. • Design and implement agentic or AI-assisted solutions that enhance data management processes, including: • Implement and maintain automated metadata ingestion, lineage, stewardship, and documentation workflows. • Work closely across governance, quality, architecture, and platform disciplines to deliver cohesive data management solutions. • Data quality rule creation and monitoring • Translate data management standards and requirements into concrete technical implementations. • Ensure metadata standards are consistently applied to support data discovery, trust, and reuse. • Develop automation that captures technical and business metadata as data is ingested into the Enterprise Data Lake. • Partner with data governance, data quality, and architecture counterparts to embed policies, standards, and controls into catalog-driven workflows. • Help ensure data management considerations are addressed early in the data lifecycle. • Support the evolution from manual, reactive processes to scalable, automated data management capabilities.

Key Responsibilities

• ▸catalog admin
• ▸metadata ingestion
• ▸data quality
• ▸ai solutions
• ▸automation workflows
• ▸governance collaboration

What You Bring

• Agentic & Intelligent Data Enablement • Hands-on experience with cloud-based data platforms, preferably AWS (e.g., S3, Glue, Athena, Redshift, Lake Formation, or similar). • Experience in Agile environments or working with cross-functional teams in iterative, fast-paced delivery cycles. • Exposure to data quality frameworks or AI-driven data quality tooling. • Collaborative: You work well across disciplines, value shared ownership, and help reinforce a “one team” mindset within Data Management. • Systems Thinker: You understand how metadata, governance, quality, and architecture work together to support analytics and data products. • Detail-Oriented: You have a passion for ensuring data accuracy, consistency, and long-term sustainable data management. • Experience in data engineering, analytics engineering, or data platform–focused roles. • Experience working with data catalogs or metadata management tools (Alation preferred). • Experience in a federated or hybrid data governance model. • Ability to collaborate effectively within a cross-disciplinary data management organization. • Experience working in data governance or data product–oriented operating models. • Working knowledge of data management concepts including metadata, lineage, data quality, and access controls. • Proficiency with SQL and at least one programming language (e.g., Python) • Continuous Learner: You are curious about emerging tools, patterns, and AI-driven approaches to data management. • Hands-On Builder: You enjoy writing code, configuring platforms, and automating processes rather than defining concepts alone. • Familiarity with automated data ingestion pipelines and metadata-driven architecture.

Requirements

• ▸aws
• ▸alation
• ▸sql
• ▸python
• ▸agile
• ▸data quality

Work Environment

Office Full-Time