Big Data Engineer
1 week ago
Experience in developing and delivering scalable big data pipelines using Apache Spark and Databricks on AWS.
Position Requirements :
Must Have : Build and maintain scalable data pipelines using Databricks and Apache Spark. Develop and optimize ETL/ELT processes for structured and unstructured data. Knowledge of Lakehouse architecture for efficient data storage, processing, and analytics. Orchestrating ETL/ELT Pipelines: Design and manage data workflows using Databricks Workflows, Jobs API. Worked with AWS Data Services (S3, Lambda, CloudWatch) for seamless integration. Performance Optimization: Optimize queries using pushdown capabilities and indexing strategies. Worked on data governance with Unity Catalog, security policies, and access controls. Monitor, troubleshoot, and improve Databricks jobs and clusters. Exposure to end-to-end implementation of migration projects to AWS Cloud AWS & Python Expertise with hands-on cloud development. Orchestration: Airflow Code Repositories: Git, GitHub. Strong in writing SQL Cloud Data Migration: Deep understanding of processes. Strong Analytical, Problem-Solving & Communication Skills
Good to have Knowledge / Skills : Experience in Teradata, DataStage , SSIS Knowledge of Databricks Delta Live Table. Knowledge of Delta Lake. Streaming: Kafka, Spark Streaming. CICD: Jenkins IaC & Automation: Terraform for Databricks deployment.
Educational Background : BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA
Certification : Amazon Web Services (AWS) certifications (AWS certified Data Engineer is recommended). Databricks Certified Associate Developer for Apache Spark
Drop resume to Mail id-sailaja.-
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