Lead Data Engineer

• 8+ years in data engineering, analytics engineering, or platform engineering. \n

• 3+ years in a lead/senior engineering or data platform role. \n

• Strong experience with Azure and Databricks/Lakehouse environments. \n

• Hands-on experience with SQL, Python/PySpark, data pipelines, and orchestration. \n

• Strong understanding of CI/CD and Azure DevOps. \n

• Experience with tools such as ADF, Airflow, Dagster, dbt, Terraform, GitHub Actions, or GitLab. \n

• Strong communication, collaboration, and technical leadership skills. \n

• Experience in insurance, financial services, healthcare, or other regulated environments is a plus. \n

• This is a brand-new DataOps leadership role created to help build and formalize DataOps function from the ground up. With major investments in cloud data, analytics, and AI, the company needs someone who can bring greater structure, consistency, automation, and operational discipline to its growing data environment. \n

• You’ll be a hands-on technical leader working across Data Engineering, DevOps, Enterprise Architecture, Information Management, Security, Infrastructure, and BI teams. The focus is not simply managing people, but building the DataOps practice, establishing CI/CD and engineering standards, improving pipelines, and helping teams operationalize data solutions effectively. \n

• The environment is centered around Azure and Databricks, with technologies including SQL, Terraform, Azure DevOps, ETL tools, and on-prem/cloud data platforms. \n

• This role is ideal for a self-starter who can wear multiple hats: part DataOps leader, part architect, part hands-on practitioner, and part change agent. Strong communication and collaboration skills are equally important as technical depth. \n

• In short: you’ll have the opportunity to build the DataOps function from the ground up and shape how data engineering is delivered and operated across the organization. \n

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• Build and evolve the DataOps operating model, standards, and best practices. \n

• Lead CI/CD, automation, orchestration, monitoring, and data quality initiatives. \n

• Partner with Data Engineering, Architecture, Analytics, AI/ML, DevOps, Security, and Infrastructure teams. \n

• Improve reliability, scalability, performance, and operational consistency of data platforms. \n

• Drive cloud cost optimization and operational excellence. \n

• Provide technical leadership, mentor engineers, and help shape the future DataOps organization. \n

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\n, A reasonable, good faith estimate of the minimum and maximum base salary for this position is $140k to $160K . This position will also include a discretionary bonus or 10% that generally will be depending on a variety of factors. Employee benefits will also be available, and details are available like Pension/401K/ Paid Vacation/ Life, Medical & Dental insurance etc.