[DXCSynergy] Data Engineer - Treasury

We are looking for a Data Engineer to design, develop, and maintain robust data pipelines for Deposits and Treasury applications, working with large-scale datasets and enabling financial reporting and analytics use cases. Responsibilities

Design, develop, and maintain robust data pipelines for Deposits and Treasury applications.

Work with large-scale structured and unstructured datasets using Apache Spark / PySpark.

Develop high-quality, reusable, and efficient code in Python.

Collaborate with business stakeholders to understand data requirements related to treasury products, liquidity, and deposits.

Build and optimize ETL/ELT processes for data ingestion, transformation, and integration.

Support data modelling for financial reporting and analytics use cases.

Create and maintain data visualizations and dashboards using tools such as Amazon Quicksight, Power BI, Tableau, etc.

Ensure data quality, governance, and compliance with financial regulations.

Troubleshoot performance issues and optimize data workflows.

Work closely with cross-functional teams including analysts, architects, and product owners.

Must have

At least 6 years of experience in Data Engineering space.

Strong experience building and maintaining data pipelines for banking data domains.

Hands-on expertise with Apache Spark / PySpark for large-scale data processing.

Strong Python development skills with emphasis on reusable, efficient code.

Solid ETL/ELT engineering experience (ingestion, transformation, integration).

Experience supporting data modelling for reporting/analytics use cases.

Exposure to BI/dashboarding tools such as Amazon Quicksight, Power BI, Tableau (or similar).

Practical experience with data quality, governance, and working in regulated environments.