Full Stack Data Engineer Python, React, Snowflake & Azure

About the Company

Greetings from Teamware Solutions a division of Quantum Leap Consulting Pvt. Ltd

Teamware Solutions (a division of Quantum Leap Consulting Pvt. Ltd.) is a 20+ year industry leader providing IT staffing and consulting services, supporting 4000+ professionals across India, the USA, the Middle East, and APAC for leading GCC clients.

About the Role

We are hiringa Full Stack Data Engineer – Python, React, Snowflake & Azure

• Location: Chennai, Bangalore, Hyderabad, Pune, Mumbai, Noida, Trivandrum
• Work Model: Hybrid
• Experience: 6 to 9 years
• Notice Period: Immediate - 15 days

Data Engineering - Full Stack Engineer

Experience: 8+ years | Function: Data Management & Engineering | Type: Full-time | Location: Hybrid

ROLE OVERVIEW

We are looking for an AI-forward Full Stack Engineer who is comfortable working across the data lifecycle -from source ingestion and transformation through database design, APIs, and modern front-end experiences. The strongest candidates will bring experience working with investment-management data and understand how core data domains such as positions, transactions, pricing, market data, security master, reference data, account data, and related investment data fit together to support front-office use cases

REQUIRED SKILLS & EXPERIENCE

• Approximately 6-8 years of professional software engineering experience, with meaningful hands-on experience across both backend/data engineering and front-end development.
• Experience using modern AI development tools such as Codex, Claude, Cursor, GitHub Copilot, or similar tools, with an interest in incorporating AI meaningfully into day-to-day software development.
• Strong programming skills in Python, with experience building production-quality data pipelines, services, or applications.
• Experience developing modern web applications using React and JavaScript/TypeScript.
• Strong SQL skills and practical experience designing, querying, and optimizing relational or analytical database structures.
• Experience building data pipelines involving ingestion, transformation, validation, and delivery of large or complex datasets.
• Experience developing or consuming REST and/or GraphQL APIs.
• Working knowledge of cloud-based data environments and modern data warehouses.
• Experience with Azure, Snowflake, and Azure Kubernetes Service (AKS) is required.
• Strong understanding of the full data lifecycle: source -> ingestion -> transformation -> database curated datasets -> API / application / analytics consumption.
• Demonstrated ability to troubleshoot data issues across multiple layers, including source data, transformations, databases, APIs, and user-facing applications.
• Experience working in asset management, investment management, capital markets, or similarly data-intensive financial environment.
• Familiarity with the core data concepts that underpin front-office investment workflows, including positions / holdings, transactions, pricing, market data, security master, reference data, account and portfolio data, and risk or analytics data.
• Ability to understand how these data domains relate to one another and how they are consumed by Portfolio Managers, Traders, Risk professionals, and investment analytics users.
• Comfortable working in a fast-paced engineering environment with shared ownership of production systems.
• Domain knowledge in front-office workflows, including risk, trading, and positions. Familiarity with accounting systems is mandatory

Nice-to-haves

• Experience supporting Portfolio Management, Trading, Risk, or other front-office investment
• workflows directly.
• Experience with private markets, alternatives, or Private Equity data.
• Experience with Snowflake performance optimization and data modeling.
• Experience with near-real-time or event-driven financial data.
• Familiarity with Spark or other distributed data-processing frameworks.
• Experience developing semantic or analytics-ready datasets for tools such as Tableau, Power BI,
• Sigma, or Pyramid.
• Exposure to AI/LLM application development, including retrieval, tool use, agents, structured outputs, or natural-language interfaces over enterprise data.
• Java experience in addition to Python.

Senior Full Stack Data Engineer with strong Python + SQL + Snowflake + Azure/AKS, hands-on React/TypeScript and API development, strong data pipeline experience, and investment/asset-management domain knowledge including accounting and front-office workflows.

Please let me know if you are interested in this position and send me your resume to [Confidential Information]