Experience: 6 – 8 Years

Location: Pune

Employment Type: Full-Time

Job Summary:

We are looking for a skilled and experienced PySpark Data Engineer to join our growing data engineering team. The ideal candidate will have 6–8 years of experience in designing and implementing data pipelines using PySpark, AWS Glue, and Apache Airflow, with robust proficiency in SQL. You will be responsible for building scalable data processing solutions, optimizing data workflows, and collaborating with cross-functional teams to deliver high-quality data assets.

Key Responsibilities:

· Design, develop, and maintain large-scale ETL pipelines using PySpark and AWS Glue.

· Orchestrate and schedule data workflows using Apache Airflow.

· Optimize data processing jobs for performance and cost-efficiency.

· Work with large datasets from various sources, ensuring data quality and consistency.

· Collaborate with Data Scientists, Analysts, and other Engineers to understand data requirements and deliver solutions.

· Write effective, reusable,



and well-documented code following best practices.

· Monitor data pipeline health and performance; resolve data-related issues proactively.

· Participate in code reviews, architecture discussions, and performance tuning.

Requirements

Requirements:

6 - 8 years of experience in data engineering roles.

· Solid expertise in PySpark for distributed data processing.

· Hands-on experience with AWS Glue and other AWS data services (S3, Athena, Lambda, etc.).

· Experience with Apache Airflow for workflow orchestration.

· Solid proficiency in SQL for data extraction, transformation, and analysis.

· Familiarity with data modeling concepts and data lake/data warehouse architectures.

· Experience with version control systems (e.g., Git) and CI/CD processes.

· Ability to write clean, scalable, and production-grade code.

Benefits

Benefits

Company standard perks.

📌 Pyspark Aws Glue Developer Pune
🏢 DataEconomy
📍 Pune