Senior Data Engineer Hadoop to Databricks Migration
Location: Remote
Employment Type: W2
Job Description
We are looking for an experienced Senior Data Engineer with strong hands-on experience in Hadoop to Databricks migration.
The candidate will be responsible for migrating legacy Hadoop, HDFS, Hive, and Spark workloads to Databricks and modernizing existing data pipelines using PySpark and Delta Lake.
Key Responsibilities
• Migrate Hadoop and HDFS workloads to Databricks.
• Analyze existing Hadoop, Hive, and Spark environments.
• Migrate large-scale datasets and Hive tables to Databricks.
• Convert legacy Hive, MapReduce, and Spark jobs to PySpark.
• Build and maintain ETL/ELT pipelines using Databricks.
• Develop data solutions using Python, PySpark, Spark SQL, and SQL.
• Implement Delta Lake and Databricks Lakehouse solutions.
• Perform source-to-target data mapping and transformation.
• Validate migrated data for accuracy and completeness.
• Troubleshoot data migration and pipeline issues.
• Optimize Spark and PySpark jobs for performance.
• Support migration testing, production deployment, and post-migration validation.
• Work with architects and engineering teams during the migration process.
• Document migration processes and technical solutions.
Required Skills
• 8+ years of Data Engineering or Big Data experience.
• Strong Hadoop to Databricks migration experience.
• Strong experience with Hadoop, HDFS, Hive, and Spark.
• Hands-on experience with Databricks.
• Strong Python, PySpark, Spark SQL, and SQL skills.
• Experience converting legacy Hadoop workloads to Databricks.
• Strong ETL/ELT pipeline development experience.
• Experience with Delta Lake and Databricks Lakehouse.
• Experience with data validation and reconciliation.
• Strong Spark performance tuning experience.
• Experience with Git and CI/CD.
• Strong troubleshooting and communication skills.
Preferred Skills
• Cloudera or Hortonworks to Databricks migration experience.
• Unity Catalog.
• Databricks Workflows and Jobs.
• Auto Loader and Delta Live Tables.
• AWS, Azure, or Google Cloud Platform experience.
• Hadoop modernization and decommissioning experience.