Associate, Data Engineer Workplace Data & Insights
BlackRock is hiring an Associate, Data Engineer Workplace Data & Insights in Gurugram, India. Level rates it ; you can apply on Level.
AI in this role
Build trusted data models, analytical products, and self-service datasets for workplace data and insights.
About this role
Your Team:
Enterprise Services provides strategic workplace solutions and robust infrastructure to deliver a consistent employee experience globally. Our team spans real estate strategy, workplace operations and facilities management, risk and resilience, corporate security and executive operations, and workplace experience and insights.
Your role and impact:
Your role will shape the trusted data foundations and analytical products that support both Enterprise Services and Digital Workplace. Working closely with a pipeline engineer, you will understand workplace data requirements, help translate source data into reliable analytical models and reports, and turn data from our physical workplaces and digital employee environment into actionable insights. You will focus on building effective dashboards, reports and the underlying datasets which can be accessed through self-service and via AI tools. Your efforts will enable dependable reporting, self-service analytics and actionable insight into how we operate globally for nearly 30,000 employees.
As a Data Engineer, you will:
- Develop and optimize trusted data models and shared semantic models that standardize core entities, dimensions and metrics across physical and digital workplace reporting.
- Create and maintain Power BI datasets, dashboards, reports and analytical tools that enable leaders and operational teams to understand employee experience, technology performance, space utilization and workplace operations.
- Enable secure self-service analytics and responsible data use through reusable datasets, clear documentation and appropriate access controls, aligned with privacy, audit and InfoSec standards.
- Implement data quality, lineage, testing and observability controls, investigating issues and working with source-system owners to resolve root causes.
- Define, develop and maintain automated, monitored and well-documented analytical transformations and reporting processes, partnering with the pipeline engineer on upstream dependencies to improve reliability, refresh performance and time from source data to decision-ready insight.
- Partner with a pipeline engineer to define data ingestion, integration and transformation requirements across digital workplace platforms, workplace technology, occupancy and space systems, facilities and operational sources.
- Partner with product managers, analysts, technology teams and workplace stakeholders to translate business questions into clear technical requirements and reliable data solutions.
What you'll need:
- 3–6 years of experience in business intelligence, analytics engineering, data engineering or a related discipline, including delivery of production-grade data and reporting solutions.
- Knowledge of data visualization best practices and design principles to create clear, engaging insights that communicate the story, highlight what matters and support decision-making.
- Strong SQL skills and practical experience designing, querying and optimizing relational, dimensional and analytical data models.
- Experience partnering with data or pipeline engineers to specify source, ingestion, transformation and integration needs across APIs, files, databases and cloud platforms, and to validate that resulting datasets meet analytical requirements.
- Experience developing Power BI semantic models, reports and dashboards, including Power Query and performance optimization.
- Understanding of software engineering practices including version control, testing, deployment, monitoring and technical documentation.
- Ability to analyze complex datasets, identify quality issues and trends, and explain technical findings clearly to business and technology stakeholders.
- Strong collaboration and problem-solving skills, with the ability to gather requirements and deliver maintainable solutions that support business outcomes.
Technical knowledge preferred:
- Hands-on experience with Microsoft Fabric, Azure data services and related Microsoft analytics tooling.
- Experience with Python or another scripting language for data transformation, automation and quality validation.
- Knowledge of workplace data domains such as Microsoft 365 and endpoint experience, service management, occupancy, space, building, facilities or employee experience data.
- Familiarity with metadata management, data catalogs, master and reference data, privacy, security and role-based access controls.
- Understanding of APIs, workflow orchestration, CI/CD and modern cloud data architecture patterns.
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.
Guidance on AI use for candidates
At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.
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.
To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.
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.
How we rate this
Associate, Data Engineer Workplace Data & Insights at BlackRock rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
- Tell me about a project where sql was part of your work. What did you do?
- Tell me about a project where analytics was part of your work. What did you do?
- Walk me through how you've used Power Bi in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Engineering, Data Modeling, SQL, Analytics, and Power Bi. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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