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Data Engineer – AWS Native Data Platforms, Vice President

Singapore, Singapore

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Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
Apply at BlackRock

What you’ll work on

Full posting

We are looking for a Data Engineer to join BlackRock’s Information Security 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.

  • Design, build, and maintain AWS-native data pipelines for batch and event-driven workloads

  • Develop data workflows in Apache Airflow with Python and SQL transformations

  • Integrate data from enterprise sources, including security and operational telemetry

  • Embed data quality, lineage, and observability into pipelines

  • Document data products, pipelines, and operating procedures

From the employer’s posting
We are looking for a Data Engineer to join BlackRock’s Information Security 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.
Design, build, and maintain AWS‑native data pipelines for batch and event‑driven workloads
Develop and operate data workflows using Apache Airflow for orchestration and Python and SQL for transformation and data quality logic.
Integrate data from a variety of enterprise sources, including cloud services, internal platforms, APIs, and security/operational telemetry.
Embed data quality, lineage, and observability into pipelines using testing frameworks and monitoring standards.
Document data products, pipelines, and operating procedures to support transparency and long‑term maintainability.

Tools in this posting

  • Python
  • SQL
  • AWS
  • dbt
  • Elasticsearch
  • S3
  • Terraform
  • Airflow
  • Great Expectations
Source — Tool mentions in context
- Design, build, and maintain AWS‑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).
- Orchestration: Apache Airflow - Languages: Python, SQL - Data Modeling & Transformation: Analytics‑engineering patterns (e.g., dbt‑like workflows)
- 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).
What You’ll Do - Design, build, and maintain AWS‑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.
Core Technologies You’ll Work With - AWS: S3, IAM, Glue, Lambda, Step Functions, CloudWatch, Secrets Manager, OpenSearch, and related native services - Orchestration: Apache Airflow
- 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.
- 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.
- 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)
- 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.
- 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
- AWS: S3, IAM, Glue, Lambda, Step Functions, CloudWatch, Secrets Manager, OpenSearch, and related native services - Orchestration: Apache Airflow - Languages: Python, SQL
- 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.
- 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)

Benefits in the posting

Full benefits wording
  • 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.
  • Guidance on AI use for candidates

From the employer’s posting.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being.

In the employer’s words · Read in context

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Sep 9, 2026 · 46 days ago
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Last seen by us
Oct 25, 2026

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Job description

View original posting ↗

About this role

About the Role

We are looking for a Data Engineer to join BlackRock’s Information Security 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 maintain AWS‑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

  • 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.

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.


Guidance on AI use for candidates


At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.


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.


To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.

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.

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Location & working pattern

Singapore, Singapore

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. Guidance on AI use for candidates
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