Data Engineering Specialist – WFH

About the Company GlobalLogic is a digital engineering company that helps organizations design and build products, platforms, and digital experiences. As part of the Hitachi Group, the company works with clients across industries including financial services, healthcare, manufacturing, communications, automotive, and technology. About the Role The Lead Data Engineer will strengthen data engineering practices across Python, Spark, and Databricks, with a focus on production-ready pipelines, automated testing, and reliable deployment processes. The role also involves reviewing existing architecture, improving data modeling and governance practices, and introducing practical AI and large language model (LLM) engineering capabilities. This position suits an experienced engineer who can work effectively in an evolving codebase, establish reusable engineering patterns, and help teams maintain those practices independently. Key Responsibilities Build and maintain production-grade data pipelines using Python, Spark, and Databricks, following sound software engineering practices such as modular development, packaging, and code review.Apply Delta Lake and medallion architecture principles, with familiarity with Databricks Asset Bundles.Develop automated tests using pytest and code coverage tools, integrating them into GitHub Actions as deployment gates.Establish reliable CI/CD practices, including dependency pinning, lockfiles, and automated checks that prevent deployments when tests fail.Define and improve schema and data contracts, medallion architecture boundaries, idempotent reprocessing, versioning, and data lineage.Assess existing data architecture, identify weaknesses, and recommend prioritized improvements through a clear, actionable backlog.Apply AI and LLM engineering practices, including token and cost instrumentation, batching, concurrency controls, model selection, and model serving.Create reusable engineering patterns, documentation, and written playbooks that enable teams to maintain and extend solutions after the engagement.Work effectively within a fast-moving codebase and help improve engineering standards without relying on a greenfield environment. Required Qualifications Bachelor's or master's degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.Production-level Python development experience with Spark or Databricks.Experience building maintainable data pipelines using software engineering practices such as modular code, packaging, and code review.Knowledge of data engineering and modeling concepts, including schema contracts, data lineage, versioning, and idempotent processing.Experience with automated testing and CI/CD, particularly pytest, code coverage, and GitHub Actions.Familiarity with Delta Lake, medallion architecture, and Databricks Asset Bundles.Experience with AI or LLM engineering, including practical considerations such as usage costs, batching, concurrency, model selection, and serving.Ability to evaluate architecture, prioritize improvements, and document repeatable engineering practices. Salary & Benefits The estimated annual base salary range is $130,000–$135,000. The final offer may vary based on qualifications, experience, business needs, responsibilities, internal equity, and other relevant factors. GlobalLogic offers health and life insurance, short-term and long-term disability insurance, flexible spending accounts, paid time off, and holidays. Employees also have access to flexible work schedules, work-from-home opportunities, continuing education, professional certifications, technical training, and international knowledge-sharing opportunities.