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BlackRock

Data Platform Engineering, BlackRock Global Markets, Director

Reposted 13 Hours Ago
Be an Early Applicant
In-Office
Gurugram, Haryana
Expert/Leader
In-Office
Gurugram, Haryana
Expert/Leader

About this role

About the role

The Lead – Data Platform Engineering will architect and build the data infrastructure that underpins our markets & investment analytics.   This role is responsible for designing scalable data frameworks, integrating firm-wide data assets, and enabling teams to deliver data solutions efficiently and safely. Working within BlackRock’s Global Markets & Index Investments (BGM) Data & Analytics team – the Lead will spearhead the creation of our next-generation data ecosystem using DevOps practices, helping shape analytics that power its critical market and investment systems. As a leader, this position demands a balance of hands-on execution, strategic direction, and team leadership to ensure a reliable, scalable, and secure data platform.
 

Experience & Education

  • 10+ years in backend, data, or platform engineering (with at least 3–5 years dedicated to data infrastructure and cloud-native architecture). Proven track record of building internal data platforms or developer tools at scale is highly desirable.

  • A Bachelor’s degree or equivalent experience in Computer Science, Engineering, or related discipline is a must. Proficiency in data architecture protocols and previous involvement with financial or investment data systems is beneficial.
     

Success Metrics

  • Reduced time to build and deploy data pipelines.

  • Increased adoption of common tooling across teams.

  • High system reliability and observability coverage.

  • Migration away from legacy to more modern, cloud native and AI-friendly data architecture
     

Required Skills

Technical

  • Distributed systems expertise: Profound understanding of distributed data systems and advanced data technologies (e.g. SparkKafkaAirflow) for large-scale data processing. 

  • DevOps & Cloud proficiency: Expertise in implementing CI/CD pipelines, cloud orchestration, and infrastructure-as-code(Terraform, CDK) on modern cloud platforms (Azure preferred, also AWS/GCP). Hands-on experience with containerization (Docker, Kubernetes) and cloud infrastructure automation is essential. 

  • Data pipeline development: Proficiency in designing and optimizing scalable data pipelines for data ingestion, transformation, and delivery. Experience with modern ETL/ELT frameworks (e.g. Apache Airflow, dbt, Azure Data Factory) for workflow orchestration is preferred. 

  • Programming & data modelling: Strong programming skills in Python, SQL, Scala with solid data modelling and database design experience. Ability to ensure data quality, integrity, and lineage throughout data pipelines is required. 

  • Data migration experience: Proven experience leading large-scale data migration initiatives from on-premises databases (e.g. Oracle, Teradata, SQL Server) to cloud-based data platforms like Snowflake, with minimal downtime and no compromise on data integrity or compliance. 

  • Modern data architecture understanding: Familiarity with modern data architecture patterns (streaming data, data lakes, etc.) and technologies. Ability to build resilient data services supporting advanced analytics, AI/ML models, and event-driven use cases. 
     

Leadership & Strategy

  • Demonstrated ability to lead and mentor engineering teams, establish high coding standards, and drive continuous improvement in platform reliability and developer efficiency.

  • Excellent collaboration and communication skills, with comfort in bridging technical and business needs to deliver results!

  • Establish standards methodologies such as CI/CD pipelines, observability, and version control for data workflows.

  • Partner with Data Quality, DevOps, and Infrastructure teams to ensure seamless data flow and governance across the platform.

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

Airflow
AWS
Azure
Cdk
Docker
GCP
Kafka
Kubernetes
Python
Scala
Snowflake
Spark
SQL
Terraform

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