Data Engineer, Associate

About this role

Job Background

The Analytics and Automation team within the EMEA Core COO organisation leverages technology, data, and AI to deliver management information and analytics that drive actionable insights into sales performance and client engagement across the EMEA client businesses. The team plays a critical role in shaping how BlackRock sells to and services its clients, enabling better decision‑making through the effective use of data.

The team partners closely with Technology and Engineering teams to design and deliver high‑impact data and visualisation tools for COO and Distribution stakeholders. You will also collaborate with internal technology teams on infrastructure, tools, processes, standards, and development practices, as well as work alongside data science and analytics teams across the firm.

The successful candidate will bring a strong passion for technology, data, and client outcomes, with comfort working across a broad range of technical capabilities, including databases, software development, and cloud infrastructure. This role suits someone who enjoys solving complex problems and building scalable, high‑impact data products.

At BlackRock, we value curiosity, continuous learning, and professional growth. With over $14 trillion in assets under management, we have a unique responsibility: our products and technology empower millions of investors to save for retirement, pay for education, purchase homes, and improve their long‑term financial wellbeing.

Key Responsibilities

• Explore, profile, cleanse, and preprocess data to ensure high‑quality datasets for analytics, reporting, and downstream consumption.
• Design and manage workflows for storing and retrieving vectorised documents to support AI‑enabled use cases.
• Apply embedding models to build AI‑driven solutions.
• Leverage modern AI and machine‑learning techniques, including large language models (LLMs) and agent‑based systems, to enhance data workflows and automation.
• Design, build, and maintain scalable ELT pipelines in Snowflake, covering data ingestion, transformation, and publication layers for enterprise use.
• Develop and optimise Snowflake data models (schemas, views, and curated datasets) to enable consistent, performant, and well‑governed access.
• Implement robust data quality controls, including validation, reconciliation, monitoring, and alerting, to ensure the accuracy and reliability of critical datasets.
• Partner with central platform and data engineering teams to support Snowflake architecture, including performance tuning, warehouse optimisation, security patterns, and cost‑effective usage.
• Write high‑quality, maintainable code that is well tested, documented, and aligned with engineering best practices, including version control and peer review.
• Build and maintain Streamlit applications to enable self‑service data exploration, operational tooling, and lightweight analytics for business users, including applications that interact directly with Snowflake datasets and stored procedures.
• Translate business questions into technical solutions, delivering clear outputs and actionable insights for both technical and non‑technical stakeholders.

Skills and Competencies

• Strong experience with Snowflake and advanced SQL, including query optimisation and best‑practice analytical data modelling.
• Knowledge of modern AI and machine‑learning techniques, including large language models (LLMs) and agent‑based systems, embedding modes and document vectorization
• Experience developing and maintaining data transformation workflows using dbt within Snowflake, including modular modelling, testing, and documentation.
• Proficiency in Python for data engineering and application development, including data processing, orchestration patterns, and reusable components.
• Experience building Streamlit applications, ideally in an enterprise environment, with a focus on usability and integration with Snowflake‑backed data products.
• Familiarity with modern data engineering practices, including ELT/ETL patterns, incremental processing, scheduling, observability, and automated testing.
• Strong problem‑solving mindset, with the ability to work independently, manage ambiguity, and drive continuous improvement.
• Strong communication skills, with the ability to articulate technical concepts and insights to non‑technical stakeholders.
• Fluency in English, both written and spoken.

Experience and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative discipline.
• Proven experience in data engineering, analytics engineering, or a closely related technical role, ideally within a cloud‑based data platform environment.
• Experience working with commercial, sales, or distribution datasets is an advantage.
• 3–5 years of relevant experience in data engineering, or a related field within a multinational or complex organisational environment

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; 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, race, religion, sex, sexual orientation and other protected characteristics at law.