Data Engineer

Crisil; Mumbai; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Crisil is seeking a Data Engineer - Python, Snowflake to build and optimize data pipelines and data structures for front-office and investment data. You will design databases across refinement stages and create APIs for efficient data access, while collaborating with Portfolio Management, Trading, Risk, and Data teams.

The role includes developing React-based interfaces for investment professionals to explore data, ensuring data quality and pipeline reliability with modern software practices.

Responsibilities

• Build and enhance data ingestion and transformation pipelines for front-office and investment data sources, including near-real-time feeds.
• Design and develop database structures across stages of refinement from source data to curated datasets.
• Work with data across investments domains including positions and holdings, transactions, pricing and valuations, market data, reference data, accounts, portfolios, investment structures, and related risk and analytics data.
• Develop APIs and data-access patterns for efficient consumption of curated datasets.
• Build React-based interfaces for investment professionals to explore, validate, and interact with data.
• Collaborate with Portfolio Management, Trading, Risk, and Data teams to translate workflows into technical solutions.
• Investigate and improve datasets and pipelines focusing on data quality, reliability, performance, lineage and downstream usability.
• Apply software engineering best practices including testing, code reviews, documentation, version control, and production validation.
• Use AI-assisted development tools to accelerate engineering, testing, documentation, and analysis.
• Explore opportunities to make trusted investment data accessible to AI assistants and AI-enabled workflows.
• Participate in production support and assist in troubleshooting data or application issues.

Job description

Data Engineer - Python, Snowflake

Front-office domain must have

• Build and enhance data ingestion and transformation pipelines for critical front-office and investment data sources, including near-real-time feeds where required.
• Design and develop database structures across multiple stages of refinement, from source-aligned data through curated, consumption-ready datasets.
• Work with data spanning core investment domains including positions and holdings, transactions, security and instrument master data, pricing and valuations, market data, reference data, accounts, portfolios, investment structures, and related risk and analytics data.
• Develop APIs and data-access patterns that allow applications and analytics workflows to efficiently consume curated datasets.
• Build intuitive React-based user interfaces that allow investment professionals and internal users to explore, validate, and interact with data.
• Partner with Portfolio Management, Trading, Risk, and Data teams to understand business workflows and translate them into well-designed technical solutions.
• Investigate and improve existing datasets and pipelines with focus on data quality and reconciliation, pipeline reliability and performance, query performance, data lineage and transparency, and usability for downstream consumers.
• Apply software engineering best practices including testing, code reviews, documentation, version control, and production validation.
• Use modern AI-assisted software development tools to accelerate engineering, testing, debugging, documentation, and analysis.
• Explore opportunities to make trusted investment data more accessible to AI assistants, agents, and other AI-enabled workflows.
• Participate in production support and help troubleshoot data or application issues when they arise.