Associate, Data Engineer

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 ex ... (truncated, view full listing at source)