Job Description
Job Summary
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We are looking for an experienced AWS Databricks Data Engineer to design, develop, administer, and optimize data platforms built on Databricks and AWS. The ideal candidate will have strong hands-on experience with Databricks, Apache Spark, AWS cloud services, data pipelines, Unity Catalog, security, infrastructure automation, and cost governance.
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The candidate will be responsible for building and supporting scalable data engineering solutions while maintaining security, reliability, performance, and operational standards.
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Key Responsibilities
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Design, develop, and maintain scalable data engineering solutions using Databricks on AWS.
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Develop and optimize data pipelines using Apache Spark, PySpark, SQL, and Delta Lake.
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Build ETL/ELT pipelines for batch and near-real-time data processing.
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Work with AWS services including S3, IAM, Glue, Lambda, CloudWatch, KMS, and VPC.
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Administer and support Databricks workspaces, clusters, jobs, notebooks, compute policies, and access controls.
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Implement and manage Unity Catalog for centralized data governance, access control, lineage, auditing, and data discovery.
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Configure catalogs, schemas, external locations, storage credentials, permissions, and workspace access.
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Implement secure integration between Databricks and AWS S3 using appropriate IAM roles and policies.
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Automate Databricks and AWS infrastructure using Terraform / Infrastructure as Code.
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Monitor and optimize Databricks cluster performance, workloads, and resource utilization.
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Implement Databricks job scheduling, monitoring, alerting, and troubleshooting.
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Establish and enforce data security, governance, and compliance standards.
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Optimize cloud and Databricks costs through cluster policies, autoscaling, job optimization, and resource monitoring.
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Support CI/CD implementation for Databricks notebooks, jobs, workflows, and code.
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Work with DevOps teams to integrate Databricks deployments with Git, CI/CD pipelines, and Terraform.
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Troubleshoot production data pipeline failures, performance issues, and infrastructure problems.
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Collaborate with data architects, application teams, DevOps, security, and business stakeholders.
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Required Skills
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12+ years of experience in Data Engineering / Big Data / Cloud Data Platforms.
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Strong hands-on experience with Databricks on AWS.
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Strong knowledge of Apache Spark and PySpark.
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Advanced SQL skills.
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Experience with Delta Lake / Delta tables.
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Strong experience with AWS S3 and IAM.
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Experience with Databricks Unity Catalog and data governance.
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Experience with Databricks administration and workspace management.
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Experience with Terraform / Infrastructure as Code.
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Experience with Git and CI/CD.
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Strong understanding of data pipeline architecture, ETL/ELT, and data warehousing.
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Experience with monitoring, troubleshooting, and performance optimization.
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Preferred Skills
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AWS Glue
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AWS Lambda
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AWS CloudWatch
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AWS KMS
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AWS VPC
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Databricks Workflows
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Databricks Jobs
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Databricks SQL
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Delta Live Tables / Lakeflow
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MLflow
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Kafka or other streaming technologies
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Python
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Scala
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Airflow
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Azure DevOps / GitHub Actions / Jenkins
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Docker / Kubernetes
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Data quality and observability tools