Sr Data Engineer

Awign; Bengaluru Urban; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Awign in Bengaluru (Bangalore North) is seeking a Data Engineer with 3+ years in data engineering or big data environments. You will develop and optimize ETL pipelines, work with AWS services, Spark, SQL, Snowflake/Databricks, and collaborate with cross-functional teams to ensure timely data delivery.

The role emphasizes data modeling, governance, and end-to-end data warehouse design, with hands-on experience in batch and streaming architectures.

Qualifications

• 3+ years of experience in data engineering or big data environments.
• Experience with AWS services like EMR, Glue and Redshift, Snowflake or Databricks.
• Hands-on with Spark (Core/SQL/Streaming) and Flink.
• Strong SQL and PySpark coding for data transformation.
• Collaborate with data architects and analytics teams to deliver data.
• Experience in data quality, governance, and monitoring processes.

Responsibilities

• Develop, maintain, and optimize ETL pipelines for batch and streaming data.
• Work with data architects to implement scalable data models and warehouse structures.
• Write efficient SQL and PySpark code for data transformation and analytics.
• Support data quality, governance, and monitoring across pipelines.
• Collaborate with business and analytics teams to understand data requirements.
• Participate in performance tuning and troubleshooting of data workflows.
• Contribute to documentation, standards, and automation across data engineering projects.

Skills

Data modeling

ETL development

Performance tuning

Data quality

Governance

Collaboration

Ownership

Customer communication

Tools

AWS

Spark

Python

SQL

Airflow

Kafka

Snowflake

Databricks

Job description

Bangalore North, India | Posted on 02/09/2026

Interview: Should be available for F2F interview after the 1st round

Experience:

3+ years of experience working in data engineering or big data environments.

Experience working with services like EMR, Glue, Redshift within AWS, Snowflake, and Databricks

Hands-on experience with AWS, Spark, Python, and SQL

Solid understanding of data modeling and data warehouse design principles

Experience with distributed data frameworks such as Spark (Core, SQL, Streaming) or Flink

Hands-on experience with Snowflake or Databricks

Experience working on setting up data warehouses/ lake or lakehouse platforms end-to-end

Industry knowledge in Retail, Logistics, FSI, or Manufacturing would be an added advantage

Develop, maintain, and optimize ETL pipelines for batch and streaming data

Work with data architects to implement scalable data models and warehouse structures

Write efficient SQL and PySpark code for data transformation and analytics

Support data quality, governance, and monitoring processes

Collaborate with business and analytics teams to understand data requirements and ensure timely data delivery

Participate in performance tuning and troubleshooting of data workflows

Contribute to documentation, standards, and automation across data engineering projects

Collaborate with cross-functional teams to ensure seamless data delivery and alignment with business goals

Key Skills:

Technologies: AWS, Spark, Python, SQL, Airflow, Kafka, Snowflake, Databricks

Frameworks: Spark Core, Spark SQL, Spark Streaming/Flink

Soft Skills: Customer communication, Team coordination, problem-solving, Ownership