About this role
As an Associate on the Analytics & Risk / Aladdin Data Cloud (ADC) team, you will be part of a group responsible for building, evolving, and operating BlackRock’s next‑generation data platforms. These platforms enable enterprise‑scale data ingestion, transformation, orchestration, and analytics to support critical investment, analytics, and risk workflows.
This is a hands‑on AI based data engineering role for a strong candiate with experience across Snowflake, SQL, Python, dbt, Airflow, AI, and cloud‑native services. The role focuses on building reliable, secure, and scalable data pipelines and transformation frameworks, while adopting modern engineering practices such as CI/CD, cloud automation, and AI‑assisted development.
You will work on Snowflake‑based data platforms integrated with Azure services, contributing to ingestion pipelines, curated data models, performance optimisation, and operational resilience. The role sits at the intersection of data platform engineering, analytics engineering, and cloud infrastructure.
A key focus of this role is applying strong engineering fundamentals to deliver high‑quality, production‑grade data solutions, while continuously improving developer productivity through automation, standardisation, and AI‑enabled tooling.
You will partner closely with senior engineers, platform leads, and cross‑functional stakeholders to deliver scalable, maintainable solutions that advance BlackRock’s enterprise data capabilities.
Responsibilities
- Design, build, and maintain end‑to‑end data pipelines on Snowflake, leveraging capabilities such as Snowpipe, Streams, Tasks, Dynamic Tables, and Virtual Warehouses.
- Develop and maintain analytics‑ready data models using dbt Core, including implementing dbt tests to ensure data quality, reliability, and trustworthiness.
- Write and optimise complex SQL for large‑scale analytical workloads, including joins, transformations, and performance‑critical queries.
- Apply Snowflake performance tuning and cost optimisation techniques, including warehouse sizing, query optimisation, and effective use of metadata and monitoring.
- Develop and maintain Python‑based components and utilities, using libraries such as pandas for data manipulation and automation.
- Build and integrate event‑driven and cloud‑native solutions using Azure Blob Storage, Event Grid, Storage Queues, and Azure Functions.
- Contribute to CI/CD pipelines and Git‑based workflows, following modern DevOps and GitOps practices for data and platform assets.
- Participate across the full development lifecycle, including requirements analysis, design, development, testing, deployment, and ongoing enhancement.
- Partner with senior engineers and cross‑functional teams to translate data and analytics requirements into robust technical solutions.
- Improve reliability, scalability, observability, and operational resilience of data pipelines and platform components.
- Adopt and apply AI‑assisted engineering practices, including AI‑enabled coding, SQL generation, testing, and documentation, where they improve quality or developer productivity.
- Contribute to engineering standards, best practices, documentation, and shared platform capabilities.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related technical field.
- 3–5 years of experience in data engineering, analytics engineering, or platform engineering roles.
- Strong hands‑on experience with Snowflake, including architecture, data ingestion, transformation, and operational best practices.
- Strong SQL skills, including complex joins, data manipulation, and performance optimisation.
- Strong knowledge about AI based development using latest models available. Ability to translate product requirements into actionable, secure, deployable code using standard devops principles, adhering to security and governance guardrails.
- Experience developing data models and tests using dbt Core.
- Solid programming experience in Python, with familiarity using pandas, numpy, datafames or similar libraries.
- Experience working with CI/CD pipelines, Git‑based workflows, and modern DevOps practices.
- Practical experience with Azure cloud services, preferably Blob Storage, Event Grid, Storage Queues, and Azure Functions.
- Understanding of security, data governance, and production‑grade engineering practices in enterprise environments.
- Strong communication and collaboration skills, with the ability to work effectively with engineers and non‑engineering partners.
- Ability to operate effectively in a fast‑paced environment and take ownership of assigned deliverables.
Preferred Qualifications
- Experience with Snowflake cost optimisation, workload management, and metadata‑driven monitoring.
- Exposure to data observability, data quality frameworks, or operational monitoring.
- Experience working on enterprise‑scale data platforms or analytics systems.
- Familiarity with event‑driven or message‑based architectures.
- Exposure to AI‑assisted development tools, LLM‑based coding assistants, or automation frameworks.
- Experience working in regulated or large‑scale financial services environments.
What success looks like
- You deliver reliable, well‑designed data pipelines and models that support high‑quality analytics and risk use cases.
- You contribute to the scalability, performance, and operational excellence of the Snowflake‑based data platform.
- You write clean, maintainable, and production‑ready code and steadily take ownership of increasingly complex components.
- You improve developer experience and platform efficiency through automation, standardisation, and AI‑assisted engineering practices.
- You build strong domain knowledge of BlackRock’s enterprise data platforms and become a trusted, hands‑on contributor within the team.
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.
