AWS Data Engineer (databricks)

Overview

Sr. AWS Data Engineer
Years of experience: 5-10 years (with minimum 5 years of relevant experience)

Work mode: WFO- Chennai (mandate)

Type: FTE

Key skills: Python,SQL,Pyspark, AWS, Databricks, SQL, Data Modelling

JD:

Essential Skills / Experience:

• 4 to 6 years of professional experience in Data Engineering or a related field.
• Strong programming experience with Python and experience using Python for data wrangling, pipeline automation, and scripting.
• Deep expertise in writing complex and optimized SQL queries on large-scale datasets.
• Solid hands-on experience with PySpark and distributed data processing frameworks.
• Expertise working with Databricks for developing and orchestrating data pipelines.
• Experience with AWS cloud services such as S3, Glue, EMR, Athena, Redshift, and Lambda.
• Practical understanding of ETL/ELT development patterns and data modeling principles (Star/Snowflake schemas).
• Experience with job orchestration tools like Airflow, Databricks Jobs, or AWS Step Functions.
• Understanding of data lake, lakehouse, and data warehouse architectures.
• Familiarity with DevOps and CI/CD tools for code deployment (e.g., Git, Jenkins, GitHub Actions).
• Strong troubleshooting and performance optimization skills in large-scale data processing environments.
• Excellent communication and collaboration skills, with the ability to work in cross-functional agile teams.

Desirable Skills / Experience:

• AWS or Databricks certifications (e.g., AWS Certified Data Analytics, Databricks Data Engineer Associate/Professional).
• Exposure to data observability, monitoring, and alerting frameworks (e.g., Monte Carlo, Datadog, CloudWatch).
• Experience working in healthcare, life sciences, finance, or another regulated industry.
• Familiarity with data governance and compliance standards (GDPR, HIPAA, etc.).
• Knowledge of modern data architectures (Data Mesh, Data Fabric).
• Exposure to streaming data tools like Kafka, Kinesis, or Spark Structured Streaming.
• Experience with data visualization tools such as Power BI, Tableau, or QuickSight.

Job Types: Full-time, Permanent

Benefits:

• Health insurance
• Provident Fund

Schedule:

• Day shift
• Monday to Friday

Application Question(s):

• Are you available for Face to Face interview on 26th July?
• Are you an immediate joiner?
• Please mention your current and expected CTC

Experience:

• Data Engineering: 5 years (Required)
• Python: 5 years (Required)
• AWS: 3 years (Required)
• pyspark: 3 years (Required)
• Databricks: 3 years (Required)

Work Location: In person