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AWS Data Engineer

AWS Data Engineer

People Prime WorldwideDelhi, India
1 day ago
Job description

Important Note (Please Read Before Applying)

Do NOT apply if :

  • You have less than 8 years or more than 10 years of total experience
  • You do NOT have strong Python + AWS Data Engineering experience
  • You are NOT hands-on with Glue / EMR / Redshift / Athena
  • You are on a notice period longer than 30 days
  • You lack real experience in building data pipelines end-to-end
  • You are from unrelated backgrounds (support / testing-only / non-data roles)

Apply ONLY if you meet ALL criteria above.

Random / irrelevant applications will not be processed.

Job Title : Senior Data Engineer – Python & AWS

Location : Hyderabad

Experience : 8–10 Years (STRICTLY)

Employment Type : Permanent

Notice Period : Immediate to 10 Days Only

About the Company :

Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future.

Job Description :

  • Architect, build, and optimize scalable data pipelines using AWS services (Glue, Lambda, EMR, Step Functions, Redshift)
  • Design and manage data lakes and data warehouses on S3, Redshift, and Athena
  • Develop Python-based ETL / ELT frameworks and reusable transformation modules
  • Integrate diverse data sources including RDBMS, APIs, SaaS, Kinesis / Kafka
  • Lead data modeling, schema design, and partitioning strategies for performance and cost efficiency
  • Implement data quality, observability, and lineage using AWS Glue Data Catalog / Data Quality or equivalent tools
  • Enforce strong data security, governance, IAM, encryption, and compliance practices
  • Collaborate with Data Science, Analytics, DevOps, and Product teams to support ML / BI workloads
  • Build CI / CD pipelines using CodePipeline, GitHub Actions, or similar
  • Provide technical leadership, mentoring, and conduct code reviews
  • Monitor and troubleshoot data infrastructure, ensuring high performance and reliability
  • Mandatory Skills :

    5–10 years of hands-on experience in Data Engineering

    Expert-level Python (pandas, PySpark, boto3, SQLAlchemy)

    Deep experience with AWS Data Services :

  • Glue, Lambda, EMR, Step Functions
  • Redshift, DynamoDB, Athena, S3, Kinesis
  • IAM, CloudWatch, CloudFormation / Terraform
  • Strong SQL, data modeling & performance tuning expertise

    Proven experience building data lakes, warehouses, ETL / ELT pipelines

    Experience with Git, CI / CD, and DevOps concepts

    Strong understanding of data governance, quality, lineage, and security

    Preferred / Nice-to-Have Skills :

  • Apache Spark / PySpark on EMR or Glue
  • Workflow orchestration tools (Airflow, dbt, Dagster)
  • Real-time streaming : Kafka, Kinesis Data Streams / Firehose
  • AWS Lake Formation, Glue Studio, DataBrew
  • Exposure to ML / Analytics platforms (SageMaker, QuickSight)
  • AWS Analytics or Solutions Architect Certification
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