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 AthenaDevelop Python-based ETL / ELT frameworks and reusable transformation modulesIntegrate diverse data sources including RDBMS, APIs, SaaS, Kinesis / KafkaLead data modeling, schema design, and partitioning strategies for performance and cost efficiencyImplement data quality, observability, and lineage using AWS Glue Data Catalog / Data Quality or equivalent toolsEnforce strong data security, governance, IAM, encryption, and compliance practicesCollaborate with Data Science, Analytics, DevOps, and Product teams to support ML / BI workloadsBuild CI / CD pipelines using CodePipeline, GitHub Actions, or similarProvide technical leadership, mentoring, and conduct code reviewsMonitor and troubleshoot data infrastructure, ensuring high performance and reliabilityMandatory Skills :
5–10 years of hands-on experience in Data EngineeringExpert-level Python (pandas, PySpark, boto3, SQLAlchemy)Deep experience with AWS Data Services :Glue, Lambda, EMR, Step FunctionsRedshift, DynamoDB, Athena, S3, KinesisIAM, CloudWatch, CloudFormation / TerraformStrong SQL, data modeling & performance tuning expertiseProven experience building data lakes, warehouses, ETL / ELT pipelinesExperience with Git, CI / CD, and DevOps conceptsStrong understanding of data governance, quality, lineage, and securityPreferred / Nice-to-Have Skills :
Apache Spark / PySpark on EMR or GlueWorkflow orchestration tools (Airflow, dbt, Dagster)Real-time streaming : Kafka, Kinesis Data Streams / FirehoseAWS Lake Formation, Glue Studio, DataBrewExposure to ML / Analytics platforms (SageMaker, QuickSight)AWS Analytics or Solutions Architect Certification