Associate, Data Analytics

BlackRock’s interview process typically starts with an online aptitude test covering quantitative, logical, and data‑interpretation questions. Successful candidates move to a technical interview focusing on SQL queries, data modeling, BI tool usage, and scenario‑based problem solving. The final round is an HR discussion that evaluates cultural fit, communication skills, and alignment with BlackRock’s values. Preparation should include hands‑on practice with Power BI/Tableau, reviewing data pipeline concepts, and understanding basic AI/ML workflows.

BlackRock promotes a high‑performance yet inclusive culture where learning is continuous and collaboration is encouraged. Employees benefit from structured mentorship, clear career ladders, and a hybrid model that balances office interaction with remote flexibility. Work‑life balance is supported through flexible time‑off, wellness programs, and a strong emphasis on employee well‑being.

Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology or related field; MBA from a Tier‑I institute (IIT/NIT/BITS/IIM/ISB/XLRI) is preferred. Minimum 5+ years of hands‑on experience in data analytics, analytics engineering or BI. Strong SQL proficiency and experience with BI tools. Minimum 60% academic aggregate (or equivalent CGPA). No active backlogs at the time of joining.

Round 1: Online aptitude/technical assessment → Round 2: Technical interview (data engineering, BI, SQL, case studies) → Round 3: Managerial interview (scenario based, business understanding) → Round 4: HR interview (culture fit, compensation discussion)

BlackRock is the world’s largest asset manager, overseeing roughly $10 trillion in assets across public equities, fixed income, alternatives, and multi‑asset solutions. With a presence in more than 100 countries, the firm combines deep investment expertise with cutting‑edge technology to help clients achieve financial well‑being. The recent HPS/BlackRock Transaction created a new Private Financing Solutions (PFS) business unit that blends BlackRock’s global scale with HPS’s flexible capital platform, delivering credit, real‑estate, CLO and GP‑LP solutions to a broad client base. The PFS team, now part of BlackRock’s Global Executive Committee, employs over 590 investment professionals and more than 1,300 staff worldwide, fostering a culture of collaboration, innovation, and rigorous risk management. The IT Data Analytics team within PFS is the backbone of data‑driven decision making. It sources, processes, and distributes data for investment analysis, portfolio management, back‑office operations, investor reporting, and regulatory compliance. As an Associate, IT Data Analytics, you will work in Mumbai’s technology hub, partnering with senior analytics engineers, business stakeholders, and offshore development teams to build robust, analytics‑ready data pipelines and visualisation solutions that power the firm’s public and private credit, CLO, and long/short credit strategies. Key responsibilities include: 1. Designing, building, and maintaining data transformation workflows and curated datasets for reporting and analytical consumption. 2. Developing interactive dashboards and reports using Sigma, Power BI, Tableau or similar BI platforms. 3. Supporting semantic modelling, metric definition, and standardised analytics outputs across business units. 4. Integrating third‑party data sources into the analytics ecosystem, ensuring data quality and consistency. 5. Preparing high‑quality, analytics‑ready inputs for AI‑enabled use cases and embedding AI‑driven insights into visualisations. 6. Applying best practices for data governance, explainability, and AI ethics. 7. Translating business requirements into technical specifications and data models. 8. Conducting ad‑hoc analysis, data validation, and troubleshooting for end‑users. 9. Collaborating with portfolio managers, risk analysts, finance, and investor relations to understand evolving reporting needs. 10. Mentoring junior team members and contributing to continuous improvement of the analytics stack. The tech stack typically includes SQL, Azure/Snowflake cloud data platforms, Power BI/Tableau/Sigma, Python for data manipulation, and exposure to machine‑learning libraries for AI‑enabled analytics. Growth prospects are strong: high performers can progress to Senior Analytics Engineer, Analytics Lead, or Product Owner roles within BlackRock’s global data and technology ecosystem. Joining BlackRock offers exposure to world‑class investment processes, a collaborative hybrid work model, and a culture that values continuous learning, diversity, and impact. Why join? BlackRock’s reputation for excellence, its commitment to employee development, and the opportunity to work on mission‑critical data products for a leading financial institution make this role a compelling step for ambitious data professionals.