Senior Data Engineer

The Senior Data Engineer is a highly hands‑on individual contributor responsible for building, operating, and improving Sinclair's enterprise data platform. This is a Snowflake-first engineering role: most of the work is performed within Snowflake and its native ecosystem. The role spans ingestion, integration, transformation, data modeling, data quality, observability, performance, cost optimization, and production support, with particular emphasis on Snowflake-native development and Snowflake Openflow.

The ideal candidate has approximately five years of progressive data engineering experience with substantial Snowflake depth, strong SQL and Python skills, and a track record of delivering reliable, well-governed data solutions in a complex enterprise setting.

This position is on-site in Hunt Valley, MD. Candidates must be local or willing to commute.

• Design, build, test, deploy, and maintain production-grade data pipelines using Snowflake-native capabilities including Snowpipe, streams, tasks, stored procedures, and functions.
• Build scalable ELT patterns and bronze/silver/gold data models that make enterprise data reliable, reusable, and easy to consume.
• Develop SQL and Python solutions for transformation, automation, orchestration, validation, and operational workflows.
• Troubleshoot production issues, perform root-cause analysis, and implement durable, maintainable fixes.

• Build, configure, operate, and troubleshoot Snowflake Openflow pipelines and connectors for enterprise data ingestion and replication.
• Develop and support integrations from relational databases, Oracle environments, traffic and operational systems, CRM platforms, and other enterprise sources.
• Implement API-based and vendor integrations using secure stages, external access integrations, authentication, and appropriate Snowflake ingestion patterns.
• Modernize legacy ETL by moving appropriate workloads to Openflow and Snowflake-native ELT patterns that improve reliability, maintainability, and efficiency.

• Build data quality and validation controls covering completeness, accuracy, freshness, reconciliation, and integration health.
• Develop monitoring and observability for ingestion, pipeline execution, data freshness, failures, and other operational conditions.
• Design pipelines for resilience, restartability, traceability, and maintainability, with clear operational ownership and documentation.

• Work deeply with Snowflake databases, schemas, warehouses, stages, integrations, roles, and other platform objects required to deliver production data solutions.
• Optimize queries, pipelines, warehouses, and data structures for performance and cost using actual workload and usage patterns.
• Apply appropriate access controls, environment separation, data protection, auditability, and governance practices in partnership with Security and data owners.
• Identify technical debt, reliability risks, unnecessary spend, and opportunities to simplify or standardize solutions.

• Build governed data foundations for enterprise reporting, analytics, operational workflows, and emerging AI and data-product use cases.
• Develop reusable data assets that support analytics applications, semantic layers, agents, and other consumption patterns without duplicating business logic.
• Participate in technical design, code reviews, releases, production support, and continuous improvement; use Git, automated deployment, testing, and documentation practices.
• Collaborate with Data Engineering, BI, Data Science, Security, Infrastructure, Finance, and…