We are looking for a highly motivated and skilled Data Engineer Key Responsibilities Build and maintain robust, scalable ETL pipelines across batch and real-time data sources. Design and implement data transformations using Spark (PySpark/Scala/Java) on Hadoop/Hive. Stream data from Kafka topics into data lakes or analytics layers using Spark Streaming. Collaborate with cross-functional teams on data modeling, ingestion strategies, and performance optimization. Implement and support CI/CD pipelines using Git, Jenkins, and container technologies like Docker/Kubernetes. Work within cloud and on-prem hybrid data platforms, contributing to automation, deployment, and monitoring of data workflows. Skills Strong programming skills in Python, Scala, or Java. Hands-on experience with Apache Spark, Hadoop, Hive, Kafka, HBase, or related tools. Sound understanding of data warehousing, dimensional modeling, and SQL. Familiarity with Airflow, Git, Jenkins, and containerization tools (Docker/Kubernetes). Exposure to cloud platforms such as AWS or GCP is a plus. Experience with Agile delivery models and collaborative tools like Jira and Confluence. Nice to Have Experience with streaming data pipelines, machine learning workflows, or feature engineering. Familiarity with Terraform, Ansible, or other infrastructure-as-code tools. Exposure to Snowflake, Databricks, or modern data lakehouse architecture is a bonus.