Data Engineer

Job Description

Key Responsibilities

• Design, develop, and maintain scalable data engineering solutions using Python, PySpark, Spark SQL, and SQL.
• Build and manage Databricks-based applications utilizing Unity Catalog, Delta Lake, Databricks Workflows, and Asset Bundles.
• Develop and maintain CI/CD pipelines using Jenkins, Git/Bitbucket, and Docker.
• Design metadata-driven and configuration-driven deployment frameworks for enterprise data platforms.
• Manage deployment automation, dependency orchestration, validation, and release processes across environments.
• Integrate enterprise platforms and services using REST APIs and metadata management tools.
• Collaborate with cross-functional teams to deliver reliable, scalable, and governed data solutions.

Required Skills

• 4+ years of experience in Data Engineering, Data Platform Engineering, or DevOps.
• Strong experience with Python, PySpark, Spark SQL, SQL, JSON, and YAML.
• Hands-on expertise in Databricks, Unity Catalog, Delta Lake, Databricks Workflows, and Databricks Asset Bundles.
• Strong experience in Jenkins CI/CD pipelines, deployment automation, and release management.
• Experience with Docker, Git/Bitbucket, containerization, and source control best practices.
• Knowledge of metadata-driven deployment frameworks, dependency management, workflow orchestration, and CI/CD automation.
• Experience integrating enterprise platforms such as Alation, SharePoint, Knowledge Graphs, Vector Databases, Semantic/Ontology platforms, and REST APIs.

Preferred Skills

• Experience working with cloud-based data platforms.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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