Position details:

Cloud Data Engineer and Data Visualization Specialist with a solid technology background and hands-on experience working in an enterprise environment, designing and implementing data warehouses, data lakes, and data marts for large financial institutions. The ideal candidate will have BI & Analytics experience along with expertise in Data Engineering, Data Pipelines, and modern AI-assisted development practices. In this role, you will work with technology and business leads to build or enhance critical enterprise applications both on-prem and in the cloud (AWS), leveraging modern data platforms such as Snowflake and Starburst for semantic layer and data virtualization solutions.

Candidates should also have experience applying AI-enabled productivity tools such as GitHub Copilot and exposure to Agentic AI frameworks, Prompt Engineering, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) concepts to drive automation and innovation. Successful candidates will possess in-depth knowledge of current and emerging technologies, demonstrate a passion for designing and building elegant solutions, and continuously explore opportunities to improve engineering efficiency through responsible adoption of AI technologies.

Roles and Responsibilities:

· Manage data analysis and data integration of disparate systems using data virtualization platforms

· Develop and implement data mesh and data fabric architectures to enable decentralized data management and access.

· Perform federated querying to access and analyze data across different data sources.

· Develop user personas and business personas in alignment with data requirements and deliver solutions that meet business needs.

· Work with business users to translate functional specifications into technical designs for implementation and deployment

· Extract, transform, and load large volumes of structured and unstructured data from various sources into AWS data lakes, SaaS solutions such as snowflake or cloud-based data warehouses.





· Leverage GitHub Copilot and AI-assisted development tools to improve productivity, code quality, documentation, and testing efficiency.

· Design and implement AI-enabled automation solutions, including Agentic AI frameworks, to enhance data engineering, reporting, and operational processes.

· Work with cross functional team members to develop prototype, produce design artifacts, develop components, perform and support SIT and UAT testing, triaging and bug fixing.

· Optimize and fine-tune data pipeline jobs for performance and scalability.

· Implement data quality and data validation processes to ensure data accuracy and integrity.

· Provide problem-solving expertise and complex analysis of data to develop business intelligence integration designs

· Convert physical data integration models and other design specifications to source codes

· Ensure high quality and optimum performance of data integration systems to meet business solutions

Job Requirements:

Bachelors’ Degree (or foreign equivalent degree) in Information Technology, Information Systems, Computer Science, Software Engineering, or related field. Experience in the financial services or banking industry is preferred.

· 5+ years of experience with data virtualization, data mesh, data fabric, and federated querying platforms such as Denodo, Starburst or OSS platforms is highly desirable.

· 5+ Years of experience working as a Report Visualization Engineer with Power BI, Tableau, or any similar Reporting Platforms with End-to-End delivery.

· 3+ Year of experience with implementation of Data Modelling, Data Governance and RLS.





· 3+ Years of experience with Enterprise Deployment Strategies and migration of legacy platform reports to modern reporting platforms.

· 2+ years of hands-on experience using GitHub Copilot or similar AI-assisted engineering tools to accelerate software development, analytics, and automation workflows.

· 2+ years of experience building or working with Agentic AI solutions, Prompt Engineering, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI governance principles.

· Extract, transform, and load large volumes of structured and unstructured data from various sources into AWS data lakes or modern data platforms like Snowflake.

· Assist Data Management Engineering Team (either for Data Pipelines Engineering or Data Service & Data Access Engineering) for ETL or BI Design and other framework related items.

· Solid understanding of data modeling, database design, and ETL principles.

· Experience working with data lakes, data warehouses, and distributed computing systems.

· Familiarity with data governance, data security, and compliance practices in cloud environments.

· Strong problem-solving skills and the ability to optimize and fine-tune data pipelines and Spark jobs for performance.

· Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

· Tableau/Power BI / Snowflake / Starburst certifications on Data related specialties are a plus.

· Power Platform experience (Power Apps, Power Automate) will be a plus.

Business Acumen – 15%: Knowledge of Banking & Financial Services Products (such as Loans, Deposits, Forex, etc.). Knowledge of Operational/MIS Reports, Risk, and Regulatory Reporting for a US Bank is a plus.

Data Skills – 25%: Must have proficiency in Data Warehousing concepts, Data Lake & Data Mesh concepts, Data Modeling, Databases, Data Governance, Data Security/Protection, and Data Access.

Tech Skills – 50%: See above

Human Skills – 10%: Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

📌 Data Service Layer AI Engineer (Bengaluru)
🏢 ToCumulus
📍 Bengaluru