Data Engineer – PySpark, Snowflake, AWS & GenAI
D4 Insight (company site, opens in a new tab)6–12 yrsHyderabadOn-siteDirect career pageEst. 18–35 LPA
Posted 11h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable data pipelines and engineering frameworks using PySpark, SQL, Python, and Snowflake.
- Implement and manage Medallion Architecture layers (Bronze, Silver, Gold) and develop data ingestion pipelines with AWS Glue, AWS Lambda, and Kafka.
- Orchestrate workflows using Apache Airflow, optimize performance of SQL queries, Snowflake workloads, and PySpark jobs, and ensure data quality and reliability.
Minimum Requirements
- 6–12 years of relevant data engineering experience.
- Strong hands-on skills in SQL, PySpark, Python, and Snowflake.
- Experience with Medallion Architecture, ETL/ELT processes, Kafka, AWS Glue, AWS Lambda, and Apache Airflow or similar orchestration tools.
- Location requirement: Hyderabad, India.
Ideal Candidate Profile
- Experienced data engineer comfortable handling end-to-end pipeline development and optimization in cloud environments.
- Familiar with implementing Medallion Architecture and orchestrating complex workflows at scale.
- Exposure to GenAI technologies (LLMs, RAG, LangChain) is a plus but not mandatory.