- At least 7 years of Information Technology experience
- At least 7 years of experience in AWS Python technologies.
- Strong expertise in:
- DBT , Python
- AWS
- PySpark
- Hands-on experience with:
- Data Ingestion pipelines
- Shell scripting
- Snowflake , oracle , SQL Server)
- Solid understanding of distributed computing concepts and data processing frameworks.
- Experience in building ETL/data pipelines for large-scale datasets.
- Proficiency in SQL and data modeling.
Preferred Qualifications:
- Hands-on experience with data lakes, data warehouses, and scalable ETL pipeline design, including batch and real-time processing architecture.
- Strong understanding and practical exposure to Agile software development methodologies (Scrum) and SDLC practices.
- Proven experience in Banking domain,
supporting use cases such as fraud detection, risk analytics, regulatory reporting, and customer insights.
- Excellent analytical, problem-solving, and communication skills, with the ability to translate business requirements into scalable technical solutions.
- Demonstrated ability to work effectively in cross-functional, multi-stakeholder environments, collaborating with Business, Data Engineering, and Architecture teams.
- Experience with real-time data streaming frameworks such as Kafka and Spark Streaming for low-latency processing.
- Understanding data modeling concepts (dimensional modeling, snowflake schemas) to support analytics workloads.
- Experience and desire to work in a global delivery environment.