Data Engineer

Role overview Build and operate the data pipelines and curated datasets that turn high-volume device telemetry and business information into reliable assets for analytics, machine learning, and AI. You’ll help mature a Databricks lakehouse, working with data science, product, DevOps, and other stakeholders on production systems and platform standards.

Responsibilities - Develop and maintain batch and streaming pipelines for telemetry and operational data. - Shape governed Bronze, Silver, and Gold data layers for analytics and AI workloads. - Package and promote production pipelines with Databricks Asset Bundles in partnership with DevOps. - Improve platform standards for governance, cost, performance, data quality, sensitivity classification, and access controls. - Prepare structured and unstructured datasets for AI applications, including vector and search-based stores.

Requirements - Five or more years of data engineering experience, including production use of Databricks. - Hands-on experience with Delta Lake, Unity Catalog, Lakeflow, Lakebase, and Asset Bundles. - Experience ingesting and modeling high-volume IoT, telemetry, or event-stream data. - Advanced Python and SQL skills, and familiarity with CSV, JSON, Parquet, and Delta formats. - A relevant bachelor’s degree or equivalent professional experience. - Strong communication skills, including the ability to explain technical concepts to nontechnical audiences.

Nice to have Experience with Databricks self-service analytics tools, property or IoT technology, SaaS platforms, data engineering certifications, Git, or Terraform.

Benefits and work setup US employee benefits include medical, dental, vision, and life insurance; flexible paid time off; a 401(k) with employer contributions; paid parental leave; and an employee stock purchase plan.