AWS Data Engineer

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:

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Experience:

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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.

• 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