Design, develop, and optimize data ingestion, transformation, and storage pipelines on AWS.
Build and maintain ETL/ELT workflows using AWS Glue, Lambda, EMR, and Step Functions.
Process and manage large-scale structured, semi-structured, and unstructured datasets efficiently.
Develop data models that align with analytical and business requirements.
Implement scalable data architectures using Python, PySpark, and Apache Spark.
Collaborate with data scientists, analysts, and business stakeholders to ensure data reliability, quality, and accessibility.
Work across on-premise and cloud data warehouses, optimizing performance and cost.
Stay current with emerging AWS data engineering tools, frameworks, and best practices.
Skills
Glue, S3, Redshift, EMR, Lambda, Step Functions, Kinesis, Athena, IAM.
Strong programming skills in Python, PySpark, and Apache Spark for data processing and transformation.
In-depth understanding of data modeling (conceptual, logical, physical) and design principles.
Experience with ETL/ELT frameworks, data governance, and data quality/security practices.
Familiarity with data warehouse systems (on-premise and cloud) and migration strategies.
Experience with Snowflake, Dataiku, or Alteryx.
Exposure to Veeva API integration (a plus, not mandatory).
Understanding of DevOps for Data Engineering -- CI/CD pipelines and Infrastructure as Code (Terraform or CloudFormation).
Job Type: Contractual / Temporary
Contract length: 6 months
Pay: ₹100,000.00 - ₹120,000.00 per month
Experience:
work: 4 years (Required)
Work Location: Remote
Beware of fraud agents! do not pay money to get a job
MNCJobsIndia.com will not be responsible for any payment made to a third-party. All Terms of Use are applicable.