Data Engineer - Research

Qode Advisors Llp; Mumbai; On-site; INR 600,000 - 900,000; Full time

Job summary

Qode Advisors Llp is hiring a Data Engineer in Mumbai to join the Research team and support data-driven investment research and analytics. You will work with large datasets, build data pipelines, and help backtesting infrastructure while developing dashboards and reporting tools for the team.

The role involves collaborating with researchers, collecting and cleaning data, and delivering reliable, visualised insights for investment decision-making.

Qualifications

• Candidate has a degree in CS/IT/DS/engineering/math/statistics or related field.
• 0–2 years of Data Engineering, Data Analytics, or related work experience; freshers welcome with strong skills.
• Solid Python and SQL knowledge with good data-structure understanding.
• Experience with Pandas/NumPy or similar data-processing libraries is preferred.

Responsibilities

• Clean, validate, and maintain financial and market datasets.
• Build data pipelines and support backtesting infrastructure.
• Develop dashboards and reporting tools for research analytics.
• Collaborate with researchers and investment teams on data requirements.
• Automate data collection and recurring reporting tasks.

Skills

Python

SQL

Data analysis

Problem solving

Communication

Team collaboration

Education

Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Mathematics, or Statistics

Tools

Pandas/NumPy

Git

Power BI

Tableau

Streamlit

APIs

Job description

We are looking for a Data Engineer to join our Research team and support the development of data-driven investment research and analytics. The role will involve working with large datasets, building and maintaining data pipelines, supporting backtesting infrastructure, and developing dashboards and reporting tools used by the Research team.

This is an excellent opportunity for someone with a strong interest in data, analytics, financial markets, and quantitative research to work closely with an investment research team.

Key Responsibilities

• Data Cleaning & Management
  • Collect, clean, validate, and maintain financial and market datasets.
  • Identify data quality issues and ensure accuracy and consistency.
  • Automate recurring data collection and updating processes.
• Support the development and maintenance of backtesting frameworks for research strategies.
• Build data pipelines and processes required for historical analysis.
• Work with researchers to improve the reliability and efficiency of backtesting systems.
• Develop and maintain dashboards for research and investment analytics.
• Convert research requirements into useful data visualisations and reporting tools.
• Ensure dashboards are accurate, updated, and user-friendly.
• Investment Reporting
  • Support the preparation and automation of investment and research reports.
  • Generate recurring performance, portfolio, and analytical reports.
  • Automate manual reporting processes wherever possible.
• Research Support
  • Work closely with researchers and investment teams on data-related requirements.
  • Perform data analysis and ad-hoc data extraction as required.
  • Support new research initiatives and contribute to improving the team's data infrastructure.

Required Skills

• Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Mathematics, Statistics, or a related field.
• 0-2 years of experience in Data Engineering, Data Analytics, or a related role; freshers with strong technical skills are welcome.
• Strong knowledge of Python and SQL.
• Good understanding of databases and data structures.
• Experience with Pandas/NumPy or similar data-processing libraries.
• Strong problem-solving and analytical skills.Ability to work with large datasets and identify data inconsistencies.
• Good communication skills and ability to work closely with non-technical stakeholders.

Good to Have

• Exposure to financial markets, capital markets, or investment research.
• Experience with APIs and automated data collection.
• Familiarity with Git and software development best practices.
• Exposure to data visualisation tools such as Power BI, Tableau, Streamlit, or similar.
• Understanding of backtesting, financial time series, or quantitative research.

What You'll Get to Work On

• Real-world financial and market data
• Research and investment analytics
• Data pipelines and reporting automation
• Cross-functional projects with the Research and Investment teams