AWS Data Engineer(Databricks)

Sr. AWS Data Engineer

Years of experience:

Work mode:

Type: Permanent

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.