Senior Data Engineer

Job Summary

• The Senior Data Engineer is responsible for designing, building, optimizing, and supporting reliable data pipelines and cloud data platform services that enable enterprise analytics, reporting, operational insights, and data-driven decision-making.
• This position requires strong hands-on experience with Azure SQL, Google Cloud Platform, BigQuery, Airbyte, Airflow, dbt, SQL, and modern data pipeline patterns. The Senior Data Engineer partners closely with analytics engineers, data analysts, software engineers, product stakeholders, and business leaders to ensure data is accurate, timely, scalable, secure, and accessible for analytical and operational use cases.
• The role balances pipeline engineering execution, platform reliability, data architecture, data quality, cost optimization, documentation, and technical mentorship while helping modernize data platform and improve confidence in enterprise data assets.

Required Experience

• 5+ years of progressive experience in data engineering, data platform engineering, analytics engineering, or a related technical role.
• Strong hands-on experience designing and supporting modern data pipelines, ELT/ETL workflows, orchestration, and cloud data warehouse solutions.
• Deep experience with SQL and relational data concepts, including Azure SQL or comparable SQL Server-based platforms.
• Hands-on experience with Google Cloud Platform and BigQuery, including dataset design, query optimization, cost management, and operational support.
• Experience with Airbyte or similar data ingestion tools and Airflow or similar workflow orchestration tools.
• Experience with dbt for transformation development, testing, documentation, lineage, and model deployment.
• Experience supporting BI and analytics consumption layers such as Looker and Google Data Studio / Looker Studio preferred.
• Experience with CI/CD, Git-based workflows, automated testing, release management, and modern DevOps practices for data assets.
• Experience in healthcare, regulated environments, SaaS platforms, or complex workflow systems preferred.