Data Engineer

Coforge is seeking a Data Engineer for their Data & AI Platform team. The role involves building and optimizing data pipelines to provide secure access to FX market data, ensuring data quality, and supporting analytics across the enterprise.

Responsibilities:

• Build robust data pipelines: Design, develop, and maintain batch and real-time data pipelines for ingesting, transforming, and storing FX data
• Enable data-driven insights: Collaborate with analysts, data scientists, and business teams to ensure timely, reliable, and well-structured data is available to support analytics and AI use cases
• Integrate market data platforms: Work with internal and external systems to ensure smooth integration of FX Spectrum data feeds using industry protocols such as FIX and REST APIs
• Support platform scalability: Contribute to the development of reusable data models, ETL frameworks, and metadata-driven pipelines across the enterprise data ecosystem (e.g., Databricks, Azure Data Factory, Power BI)
• Ensure data quality and governance: Apply rigorous data validation and quality assurance techniques, ensuring compliance with regulatory requirements and internal data governance standards
• Optimize data performance: Identify and implement performance improvements in data workflows, including indexing, partitioning, and data format optimization for large-scale FX data

Requirements:

• Bachelor's degree in computer science, Data Engineering, or related technical field
• 3–5 years of experience in data engineering or data platform development, preferably within capital markets or financial services
• Advanced proficiency in SQL and data pipeline development using tools such as Apache Spark, Databricks, or Azure Data Factory
• Experience with visualization tools such as Power BI or Tableau
• Familiarity with cloud data platforms (e.g., Databricks, Azure Synapse, or Snowflake)
• Understanding of data governance concepts and tools (e.g., Microsoft Purview, Unity Catalog)
• Strong problem-solving and system design skills with the ability to build scalable, maintainable data solutions
• Effective communicator with the ability to collaborate across technical and business teams, translating data architecture into practical use cases
• Solid business acumen and understanding of financial or credit union operations, particularly FX trading workflows and post-trade processing
• Demonstrated ability to thrive in a fast-paced, regulated, data-driven environment
• Ability to collaborate in cross-functional teams and thrive in a data-driven culture