Data Engineer Level 2

The team is seeking a Data Engineer experienced in implementing modern data solutions in Azure, with strong hands-on skills in Databricks, Spark, Python, and cloud-based DataOps practices.The Data Engineer will analyze, design, and develop data products, pipelines, and information architecture deliverables, focusing on data as an enterprise asset. This role also supports cloud infrastructure automation and CI/CD using Terraform, GitHub, and GitHub Actions to deliver scalable, reliable, and secure data solutions.Work Location must be local. Interviews will be in person, onsite. Not only do they need to be local, but they also need to be willing to come on-site for their interview, as well as that they will be expected to work on-site with the teamResponsibilitiesAnalyze, design, and develop enterprise data solutions with a focus on Azure, Databricks, Spark, Python, and SQLDevelop, optimize, and maintain Spark/PySpark data pipelines, including managing performance issues such as data skew, partitioning, caching, and shuffle optimizationBuild and support Delta Lake tables and data models for analytical and operational use casesApply reusable design patterns, data standards, and architecture guidelines across the enterprise, including collaboration with 84.51° when neededUse Terraform to provision and manage cloud and Databricks resources, supporting Infrastructure as Code (IaC) practicesImplement and maintain CI/CD workflows using GitHub and GitHub Actions for source control, testing, and pipeline deploymentManage Git-based workflows for Databricks notebooks, jobs, and data engineering artifactsTroubleshoot failures and improve reliability across Databricks jobs, clusters, and data pipelinesApply cloud computing skills to deploy fixes, upgrades, and enhancements in Azure environmentsWork closely with engineering teams to enhance tools, systems, development processes, and data securityParticipate in the development and communication of data strategy, standards, and roadmapsDraft architectural diagrams, interface specifications, and other design documentsPromote the reuse of data assets and contribute to enterprise data catalog practicesDeliver timely and effective support and communication to stakeholders and end usersMentor team members on data engineering principles, best practices, and emerging technologiesQualifications5+ years of experience as a Data EngineerHands-on experience with Azure Databricks, Spark, and PythonExperience with Delta Live Tables (DLT) or Databricks SQLStrong SQL and database backgroundExperience with Azure Functions, messaging services, or orchestration toolsFamiliarity with data governance, lineage, or cataloging tools (e.g., Purview, Unity Catalog)Experience monitoring and optimizing Databricks clusters or workflowsExperience working with Azure cloud data services and understanding how they integrate with Databricks and enterprise data platformsExperience with Terraform for cloud infrastructure provisioningExperience with GitHub and GitHub Actions for version control and CI/CD automationStrong understanding of distributed computing concepts (partitions, joins, shuffles, cluster behavior)Familiarity with SDLC and modern engineering practicesAbility to balance multiple priorities, work independently, and stay organizedRequired SkillsAzure Data BricksPythonSparkPreferred SkillsProblem solvingAttention to detailAbility to work independently and as part of an agile team

Created: 2026-05-08