Data Engineer – AWS Native Data Platforms

Technology & Operations | BlackRock

About the Role

We are looking for a Data Engineer to join BlackRock’s Technology & Operations organization, supporting the design, build, and operation of our Cloud‑native data platform that power critical technology, security, and operational use cases across the firm.

This role sits within a team responsible for building reliable, secure, and observable data pipelines in a highly regulated environment. You will work closely with technology, operations, and information security partners to deliver data products that enable transparency, automation, and risk‑informed decision making at scale.

The ideal candidate is an engineer at heart—comfortable working end‑to‑end across ingestion, transformation, orchestration, and governance—who values clean design, strong documentation, and operational excellence.

What You’ll Do

• Design, build, and maintainAWS‑native data pipelines for batch and event‑driven workloads, with a focus on reliability, scalability, and security.

• Develop and operate data workflows using Apache Airflow for orchestration and Python and SQL for transformation and data quality logic.

• Implement data transformations and models using modern analytics engineering practices (e.g., dbt‑style patterns, tested transformations, incremental processing).

• Integrate data from a variety of enterprise sources, including cloud services, internal platforms, APIs, and security/operational telemetry.

• Partner with Information Security, Risk, and Operations teams to translate business and control requirements into durable data solutions.

• Embed data quality, lineage, and observability into pipelines using testing frameworks and monitoring standards.

• Operate within BlackRock’s cloud security and governance standards, including IAM, encryption, logging, and secrets management.

• Contribute to CI/CD pipelines, infrastructure‑as‑code patterns, and standardized platform tooling.

• Document data products, pipelines, and operating procedures to support transparency and long‑term maintainability.

• Participate in design reviews, code reviews, and incident/post‑incident analysis to continuously improve platform resilience.

Core Technologies You’ll Work With

• AWS: S3, IAM, Glue, Lambda, Step Functions, CloudWatch, Secrets Manager, OpenSearch, and related native services

• Orchestration: Apache Airflow

• Languages: Python, SQL

• Data Modeling & Transformation: Analytics‑engineering patterns (e.g., dbt‑like workflows)

• Data Quality & Testing: Schema and data validation frameworks (e.g., Great Expectations‑style approaches)

• Infrastructure & Delivery: CI/CD, Git‑based workflows, infrastructure‑as‑code (Terraform or equivalent)

• Security & Governance: Encryption, access controls, audit logging, platform security baselines

What We’re Looking For

• 3-6 years experience as a Data Engineer, Analytics Engineer, or similar role building production data pipelines.

• Strong hands‑on experience with AWS‑native data services in a regulated or enterprise environment.

• Proficiency in Python and SQL, with an emphasis on readable, testable, and maintainable code.

• Experience with workflow orchestration (Airflow or equivalent).

• Solid understanding of data modeling, incremental processing, and performance optimization.

• Familiarity with data quality, monitoring, and operational support for production data systems.

• Experience collaborating with cross‑functional partners (e.g., security, operations, product, or risk teams).

• A disciplined approach to documentation, change management, and incident response.

Nice to Have

• Experience supporting security, risk, or compliance data domains.

• Exposure to OpenSearch / Elasticsearch, metrics pipelines, or log‑analytics platforms.

• Familiarity with cloud security controls, IAM design, and secrets management.

• Experience building data platforms that support executive‑level reporting or regulatory oversight.