AWS Data Engineer Data bricks

5 - 10 years

0 Lacs

Posted:5 days ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Sr. AWS Data Engineer


Years of experience:  5-10 years (with minimum 5 years of relevant experience)

Work mode: WFO- Chennai (mandate)

Type: Permanent

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


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.


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