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BlackRock

Data Operations Engineering, RQA, Associate

Posted Yesterday
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In-Office
Gurugram, Haryana
Mid level
In-Office
Gurugram, Haryana
Mid level

About this role

About this role 

 

What is the opportunity? 

 We are recruiting for Core Risk Management (Core RM) group, whose objective is to advance risk management practices at BlackRock, delivering scale and resilience to the risk management platform.  

 This opportunity is to join the Core RM team as a data governance team member, contributing to initiatives that strengthen data quality, working closely with the Core RM analytics and oversight functions, with investment risk managers globally, and with our partners across the Aladdin Data (AD) and Aladdin Financial Engineering (AFE) organizations. Core RM is part of the Risk & Quantitative Analysis (RQA) group, which provides independent oversight of BlackRock’s fiduciary and enterprise risks globally. 

  

Key Responsibilities 

  • Data Quality & Governance 

  • Monitor upstream data issues and support resolution efforts in partnership with technology and analytics teams. 

  • Contribute to reporting on data issues, resolution paths, and SLA breaches for senior management visibility. 

  • Assist in designing and implementing quality control (QC) processes for data and analytics used in risk management. 

  • Operational Support 

  • Maintain strong attention to detail and organizational skills while managing multiple priorities in a fast-paced environment. 

  • Communicate effectively across teams and levels to influence outcomes and drive improvements. 

  • Collaboration & Stakeholder Engagement 

  • Build effective working relationships with upstream teams (Aladdin Data, Aladdin Financial Engineering) to stay informed on systematic data/model changes. 

  • Support thematic issue identification and help chart resolution paths for recurring data pipeline and quality control challenges. 

  • Process Improvement 

  • Participate in the development and enhancement of governance frameworks to track and resolve data quality issues. 

  • Escalate organization-level data quality and control issues as needed. 

Qualifications 

  • Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, Finance, or a related quantitative field. 

  • 4+ Years of experience in data, analytics, or risk management within financial services. 

  • Basic proficiency in programming (SQL, Python, Unix) and/or data analytics tools. 

  • Experience with Aladdin and various datasets and calculators across Aladdin is a plus. 

  • Professional certifications (CFA, FRM) and knowledge of Aladdin are advantageous but not required. 

  • Strong attention to detail, organizational, and time management skills. 

  • High energy, motivation, and a positive approach to business challenges. 

  • Ability to explain complex ideas simply and communicate effectively with diverse stakeholders. 

  • Self-starter, ability to work in ambiguity and drive results by collaborating. 

 

What do we have? 

  • The opportunity to shape an exciting new operating model and drive adoption and application of new technology, tools, and techniques to address real business problems.  

  • A highly respected risk management group with deep subject matter expertise and global reach.  

  • A proven track record of driving better outcomes across a wide range of investment strategies and business areas.  

  • A legacy of technology innovation and deep connectivity with technology partners.  

  • A dedication to investing in our people to increase individual enablement and ultimately build a stronger team. Our goal is to create a culture of inclusion which encourages collaboration, innovation, diversity and the development of our future leaders. We actively engage in discussions on career growth and work with team members to understand how personal passions and strength connect with our purpose. 

Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being.  Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.

For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock

BlackRock is proud to be an Equal Opportunity Employer.  We evaluate qualified applicants without regard to age, disability, family status, gender identity, race, religion, sex, sexual orientation and other protected attributes at law.

Top Skills

Aladdin
Python
SQL
Unix

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