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.