⚠️ MANDATORY CRITICAL MATCH CRITERIA (READ FIRST):
✅ Experience: 2 to 4 years of dedicated experience in Data Engineering. A reliable career history with no excessive job-hopping is strictly required.
✅ Education: B.E. / B.Tech / MCA / M.Sc in Computer Science, IT, or related technical field.
✅ Core Skills: Hands-on experience executing at least TWO of the following platform-verified workflows: Data Ingestion, ETL/ELT Pipeline Development, Schema Design, Data Transformation, and Data Quality Validation.
✅ Software/Tools: Working proficiency in Python (PySpark), SQL, Java, Apache Spark, Apache Airflow, and Apache Kafka.
✅ Communication: Exceptional English skills for mandatory daily technical coordination syncs with global stakeholders.
✅ Logistics: 100% strictly Work-from-Office model located in Pune.
➡️ Position Overview
We are seeking a Jr. Data Engineer to build, optimize, and maintain scalable data pipelines and real-time streaming architectures. In this role, you will design robust ETL/ELT processes, validate data quality,
and collaborate on data modeling to support enterprise analytics and streaming systems.
? Core Responsibilities
✔️ ETL/ELT Pipeline Development: Design, build, and maintain scalable data ingestion and transformation pipelines using PySpark and SQL.
✔️ Stream Processing: Configure and manage real-time streaming architectures using Apache Kafka and Apache Spark Streaming.
✔️ Workflow Orchestration: Automate, schedule, and monitor data workflows using Apache Airflow.
✔️ Data Modeling & Warehousing: Develop logical and physical schema designs while applying core data warehousing concepts.
✔️ Data Validation & Scripting: Ensure data cleansing and quality checks while scripting in Linux/Unix environments.
How to Apply
? Please click the "Apply" button directly on this platform and ensure you accurately complete the mandatory screening questions. Applications with incomplete screening responses or profiles failing to meet the baseline experience metrics will be filtered out by our system automatically.