AWS Data Engineer

Important Note (Please Read Before Applying)

Do NOT apply if:

less than 7 years or more than 10 years

strong real-world experience with AWS Glue, Redshift, EMR, and Python

longer than 15 days

• You cannot work onsite/hybrid

non–data engineering

Apply ONLY if you meet ALL mandatory criteria above.

Random / irrelevant applications will not be processed.

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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.

Job Overview:

Senior AWS Data Engineer

AWS Glue, Lambda, EMR, Step Functions, Redshift

data lakes and warehouses

Python-based ETL/ELT frameworks

RDBMS, APIs, Kinesis/Kafka, SaaS connectors

data modeling, schema design, and partitioning

data quality, observability, and lineage

data governance, IAM policies, encryption, and access controls

Data Science, Analytics, Product & DevOps

CI/CD pipelines

technical leadership, code reviews, mentoring

• Monitor & optimize data infrastructure performance

Mandatory Skills:

AWS Data Services

– Glue, Lambda, EMR, Step Functions

– Redshift, Athena, S3

– DynamoDB, Kinesis, IAM, CloudWatch

– CloudFormation / Terraform

✔ Strong Python expertise:

pandas, PySpark, boto3, SQLAlchemy

✔ Strong SQL, performance tuning & data modeling

✔ Proven experience in:

data lakes & warehouses

ETL/ELT

streaming platforms

– Git-based workflows and CI/CD

✔ Excellent debugging, analytical & problem-solving skills

Preferred / Nice-to-Have Skills:

• Spark / PySpark on EMR or Glue

• Airflow, dbt, Dagster

• Lake Formation, Glue Studio, DataBrew

• Experience with SageMaker or QuickSight

• AWS Data Analytics or Solutions Architect Certification