Job Overview

We are seeking an experienced Cloud Data Engineer to the architecture, development, Data migration,

ETL pipeline in cloud and optimization of a next-generation data platform. This is a development role for an individual with over 4 years of deep data engineering and data migration, data pipeline in AWS expertise, capable of driving technical direction, and delivering high-impact solutions in a fast-paced

Key Responsibilities

- Platform Development

- Knowledge of best practices for our end-to-end data pipelines in Cloud, ensuring

scalability, reliability, and security across the platform.

- Aggressively folowing the project timeline to ensure rapid delivery of data migratation

in AWS RDS.

- Working with Data Analysts, and business stakeholders to translate complex

requirements into robust, production-ready ETL data solutions.

- Data Pipeline Development

- Ingestion &
- Transformation: Design, build, and optimize high-volume data ingestion and

transformation jobs using tools like dbt Core, iceberg, AWS Glue, ensuring data quality and integrity.

- Building ELT/ETL pipelines and using workflow orchestration tools like Apache Airflow or

dbt

- Optimize large-scale data processing algorithms and cloud data warehouse performance.

- Workflow: Develop and maintain sophisticated data pipelines using AWS glue/lambda,

focusing on modularity and reusability.

- Streaming &
- Real-time Integration: Implement and manage real-time data flows utilizing

native AWS streaming services (e.g., Kinesis)



for immediate data availability.

- Data Security and Privacy: Data Anonymization, Compliance with Regulations

- Good knowledge of CI/CD for ETL pipeline automation and Data

migration

- Drive the Data Ecosystem Management &
- Monitoring

- Open Table Formats &

- Management: Implement and maintain the Iceberg open table

format, utilizing tools for effective schema evolution and data management.

- Compute Engine Optimization: Optimize query performance and cost efficiency across

our primary compute engines: Amazon Redshift, and AWS Athena.

- rapidly identify bottlenecks, and troubleshoot production issues

Candidate Profile

- 4 Years of hands-on, progressive experience in Cloud Data Engineering, cloud ecosystems AWS,

Data Architecture

- Deep conceptual understanding of core data engineering principles, ETL/ELT patterns, and

metadata management

- Ability to translate complex business needs into actionable technical requirements.

- Strong troubleshooting and problem-solving skills in distributed systems.

- Agile/Scrum teamwork capabilities and version control practices

- Insurance industry experience preferred but not mandatory

- Tools:

- Cloud Environment: AWS (S3, IAM, VPC, Glue, Lambda etc.)

- Experience with dbt Core, Iceberg, AWS Glue Catalog, AWS lambda, Redshift, Athena,

Splunk, AmazonQ, AWS streaming services, Git

- Strong SQL, Pyspark and Python

Skills: dbt,glue,management,etl,aws,cloud

📌 AWS Data engineer (Pune)
🏢 CG-VAK Software u0026 Exports
📍 Pune