Cloud Data Engineer

Resource have strong data warehouse technical knowledge.

Resource have knowledge in Bank and financial domain (Minimum 12+ years of experience).

Design, develop, and maintain scalable data pipelines and workflows on AWS

Build and manage data lakes and data warehouses (e.g., S3, Redshift)

Develop ETL/ELT processes using tools like AWS Glue, Lambda, or Spark

Strong solution Knowledge in AWS Cloud and hands on experience with ETL process (like Kafka message processing, batch interface data injection and other business layer process)

Optimize data ingestion, transformation, and loading processes

Work with stakeholders to understand and deliver data requirements

Ensure data quality, governance, and security compliance

Monitor and troubleshoot data pipelines and workflows

Automate deployments using CI/CD pipelines

Improve performance, cost optimization, and scalability

Coordinate with clients, data users and key stakeholders to understand feature requirements needed merge them to create reusable design patterns

Data onboarding using the developed frameworks

Understand and make sense of available code in Netezza to design a best way to implement its current features in AWS Data Lake

Unit test code and aid with QA/SIT/Perf testing

Migration to production environment

Good to have

AWS Certifications (Solutions Architect / Data Analytics)

Experience with Airflow (or Managed Workflows for Apache Airflow - MWAA)

Exposure to Snowflake, Databricks, or Delta Lake

Amazon S3 (Data Lake)

AWS Glue (ETL)

AWS Lambda

Amazon Redshift

AWS Step Functions

AWS IAM & CloudWatch

IBM Netezza