Role & responsibilities

We are looking for a Data Engineer with solid exposure to capital markets and quantitative finance concepts, combined with handson experience in Python/R. The role involves building and maintaining data pipelines and analytical solutions and models to build indicies.

Key Responsibilities

- Quantitative Analytics Support
- Work with quants and analysts to operationalise pricing, risk, and quantitative models using Python or R.
- Prepare, transform, and aggregate timeseries data (prices, curves, vol surfaces, factors) required for valuation and risk calculations.
- Support backtesting and performance analysis for trading and investment strategies.

- Capital Markets

- Very valuable understanding of the capital markets.

- Collaboration & Delivery

- Work closely with business stakeholders to understand requirements and deliver fitforpurpose solutions.
- Collaborate with platform/DevOps teams on performance, cost optimisation, security and access controls.
- Produce and maintain technical documentation for data models, pipelines and analytics jobs.

Required Skills & Experience

- Experience
- Minimum 5 years of professional experience as a Data Engineer, Quantitative Analyst, or similar role in financial services.
- Practical exposure to capital markets.

- Technical Skills





- Strong programming experience in Python (preferred) and/or R for data processing, analysis and model implementation.
- Good knowledge of SQL for querying and optimising access to relational or cloud data stores.
- Familiarity with version control (Git) and basic CI/CD practices for data/analytics code.

- Quantitative & Domain Knowledge

- Understanding of core quantitative finance concepts such as timevalue of money, return and risk measures, probability distributions, and basic stochastic processes.
- Ability to work with timeseries financial data, yield curves, benchmarks and market indices.

Nice to Have

- Experience with cloud platforms (Azure/AWS/GCP) and related data services (e.g. Data Lake, Data Factory, Synapse/BigQuery/Snowflake).
- Knowledge of statistics and machine learning as applied to financial data.
- Knowledge of Databricks

Soft Skills

- Strong analytical and problemsolving skills with attention to detail and data quality.
- Ability to translate business and quantitative requirements into technical designs and implementations.
- Good communication skills to work effectively with the stake holders
- Proactive, ownershipdriven mindset with the ability to work in a fastpaced environment.

Preferred candidate profile

📌 Data Engineer (Hyderabad)
🏢 Innominds Software
📍 Hyderabad