Data/ETL Engineer

Ascendion Engineering; Bengaluru; On-site; INR 800,000 - 1,200,000; Full time

Job summary

Ascendion Engineering in Bengaluru, Karnataka, is seeking a Data Engineer to design, develop, and maintain scalable ETL pipelines using Python and PySpark. The role involves optimizing data workflows on AWS services such as S3, Glue, and Lambda, and ensures data quality and integrity across systems.

The ideal candidate will have solid experience with data ingestion, transformation, and validation. Familiarity with workflow orchestration tools and strong SQL skills are required. Join a dynamic team to enhance data solutions in a collaborative environment.

Qualifications

• Strong experience in Python programming.
• Hands-on experience with PySpark and Spark-based data processing.
• Solid understanding of ETL/ELT concepts and data pipeline design.

Responsibilities

• Design, develop, and maintain scalable ETL pipelines using Python and PySpark.
• Build and optimize data workflows on AWS services.
• Perform data ingestion, transformation, and validation from multiple sources.

Skills

Python programming

PySpark

ETL/ELT concepts

AWS services

SQL

Workflow orchestration

Data modeling

Version control (Git)

Job description

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines using Python and PySpark
• Build and optimize data workflows on AWS services such as S3, Glue, Lambda, Redshift, and EMR
• Perform data ingestion, transformation, and validation from multiple data sources
• Optimize data processing performance and ensure data quality and integrity
• Implement data lake and data warehouse solutions
• Collaborate with cross‑functional teams to understand data requirements
• Automate data workflows and scheduling using tools like Airflow or AWS Step Functions
• Monitor and troubleshoot data pipeline issues
• Ensure security, governance, and compliance of data systems

Required Skills & Qualifications

• Strong experience in Python programming
• Hands‑on experience with PySpark and Spark‑based data processing
• Solid understanding of ETL/ELT concepts and data pipeline design
• Experience with AWS services (S3, Glue, Redshift, Lambda, EMR, Athena)
• Proficiency in SQL and working with relational and non‑relational databases
• Experience with workflow orchestration tools (Airflow, Luigi, etc.)
• Knowledge of data modeling and data warehousing concepts
• Familiarity with version control systems like Git