Dear Candidate,

This is with reference for AWS Data Engineer Professionals

PFB the

Key responsibilities

- Inventory and baseline current Lambda functions, Dagster pipelines, dbt models, MySQL ODS flows and Kafka feeds, document lineage, schedules, SLAs and failure paths.
- Design and build Gluebased ingestion, transformation, and cataloguing patterns (Glue jobs, Glue Catalog, Crawlers) with Lambda/Step Functions/Event Bridge orchestration.
- Implement S3 Bronze landing with lifecycle/archive policies, Redshift Silver conformance and Gold canonical data products (Customer, Loan, Collections, Risk).
- Build automated dataquality gates, reconciliation checks, and sourcetoreport lineage; support the enterprise data dictionary and certification of businesscritical reports
- Implement IAM, AWSnative encryption, Secrets Manager and Goldlayer RBAC/leastprivilege access.
- Establish Dev/Test environments, Gitbased CI/CD, schema version control (Liquibase) and controlled release promotion; monitoring and recovery via CloudWatch.
- Migrate and reconcile workloads wave by wave against baselines; decommission ODS dependencies and replace reverse flows with governed interfaces.
- Optimise Redshift performance and cost (WLM, sort/Dist keys, materialised views).
- Mentor engineers, own technical quality assurance of deliverables, and work with Data Owners/Champions and Atos architects in an Agile setup.

Mandatory skills





- 10+ years in data engineering with 5+ Experience in AWS data platforms.
- Amazon Redshift (deep): data modelling, performance tuning, WLM, RBAC, external schemas/Spectrum.
- AWS Glue (jobs, Glue Catalog, Crawlers) and handson medallion (Bronze/Silver/Gold) implementation on S3 + Redshift.
- AWS Lambda, Step Functions, S3, IAM, CloudWatch, Secrets Manager.
- Advanced SQL, dimensional/canonical data modelling, ETL/ELT frameworks.
- Python (primary) PySpark for Glue jobs.
- MySQL (operational data store) and CDC/batch extraction patterns.
- dbt must be able to read, reverseengineer, and migrate existing dbt models.
- Dataquality frameworks, reconciliation, and lineage/metadata practices.
- Git,CI/CD pipelines, database schema version control (Liquibase or equivalent), Dev/Test/Prod promotion.
- Leadership, mentoring, stakeholder management; ability to work independently in Agile.

Nice to have

- Dagster orchestration for ASIS discovery and migration.
- Kafka / eventdriven streaming ingestion.
- Apache Iceberg on S3, Apache Spark/EMR
- Tableau, Metabase servinglayer knowledge.
- Infrastructure as Code (Terraform/CloudFormation).
- Datagovernance tooling (Glue Data Quality, Data Zone, Lake Formation).

Total Overall Experience-10-15years

Skill AWS Data Engineer

Location Mumbai, Chennai, and Bangalore

📌 Opportunity AWS Data Engineer professional (Bengaluru)
🏢 Atos
📍 Bengaluru