Description

Resource have strong data warehouse technical knowledge.
Resource have knowledge in Bank and financial domain (Minimum 8+ 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

MUST HAVE skills and experience for this requirement:
Amazon S3 (Data Lake)
AWS Glue (ETL)
AWS Lambda
Amazon Redshift
AWS Step Functions
AWS IAM & CloudWatch
IBM Netezza

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

Key Skills

Education

Bachelor’s degree