Data Engineer

Role: Data Engineer Location: Remote Employment Type: Full-Time Experience: 4-7 years  KEY RESPONSIBILITIES ·       Design and implement CI/CD pipelines for data pipelines (ingestion jobs) and transformation projects (e.g., dbt on Databricks, SQL, notebooks) ·       Orchestrate Databricks jobs and workflows end-to-end (ingestion, transformation, quality checks) ·       Integrate automated testing into CI/CD, including schema and contract checks for data models and tables ·       Implement FinOps best practices to support cost monitoring and allocation across the EDP ·       Automate platform operations for Databricks and related services, such as workspace and cluster provisioning, library and runtime mgmt. and job deployment/config ·       Implement and maintain identity and access management for Databricks and supporting cloud resources, including workspace- and cluster-level permissions, table- and view-level access controls (e.g., Unity Catalog or equivalent), service principals, groups, and roles for automated workloads, and RBAC & TBAC models in collaboration with EDP Architect ·       Provide patterns, templates, and reusable modules (Terraform modules, Airflow DAG patterns, Databricks job templates) to accelerate onboarding of new projects ·       Continuously evaluate and improve tooling, pipelines, and platform architecture to increase reliability, security, and developer productivity on Databricks ·       Define the code promotion process to minimize impacts across domains as code is promoted to production ·       Manage end-to-end orchestration using managed Airflow. Contribute to defining and tracking SLA/SLO/SLIs for the platform and participate in incident response (triage, root cause analysis) ·       Practical knowledge of IT Infrastructure technologies, cloud computing Azure), cybersecurity, and disaster recovery. ·       Working knowledge of Azure ecosystem, including hands-on experience designing, building, and optimizing scalable data pipelines within cloud-native environments. QUALIFICATIONS ·       Hands-on experience with Databricks in production environment, including workspace and cluster management, jobs/workflows and integrations with orchestration tools ·       Strong experience with CI/CD pipelines (e.g., GitHub Actions, GitLab CI, Azure DevOps, or similar) and Git-based workflows. ·       Strong experience with Infrastructure as Code (IaC) and orchestration tools for provisioning and managing Databricks and cloud infrastructure. ·       Experience implementing automated tests and quality gates in CI/CD pipelines. ·       Ability to partner effectively with data engineers, analytics engineers, architects, and security teams. MINIMUM EXPERIENCE & EDUCATION ·       Bachelor’s degree in Computer Science, Information Technology, or related field preferred, or equivalent work experience. ·       4–7+ years in DevOps, Cloud Engineering, Site Reliability Engineering, or Platform Engineering, with at least 2+ years supporting data/analytics platforms. ·       Experience operating production data workloads, including monitoring, logging, performance tuning, and incident response. ·       Scripting skills (e.g., Python, Bash, PowerShell) for automation and integration. ·       Experience in CPG, retail, manufacturing, or distribution environments preferred.