About this role
At BlackRock, technology has always been at the core of what we do – and today, our technologists continue to shape the future of the industry with their innovative work. We are not only curious but also collaborative and eager to embrace experimentation as a means to solve complex challenges. Here you’ll find an environment that promotes working across teams, businesses, regions and specialties – and a firm committed to supporting your growth as a technologist through curated learning opportunities, tech-specific career paths, and access to experts and leaders around the world.
We are seeking a highly skilled and motivated Senior level Data Engineer to join the Private Market Data Engineering team within Aladdin Data at BlackRock for driving our Private Market Data Engineering vision of making private markets more accessible and transparent for clients. In this role, you will work multi-functionally with Product, Data Research, Engineering, and Program management.
Engineers looking to work in the areas of orchestration, data modeling, data pipelines, APIs, storage, distribution, distributed computation, consumption and infrastructure are ideal candidates. The candidate will have extensive experience in developing data pipelines using Python, Java, Apache Airflow orchestration platform, DBT (Data Build Tool), Great Expectations for data validation, Apache Spark, MongoDB, Elasticsearch, Snowflake and PostgreSQL. In this role, you will be responsible for designing, developing, and maintaining robust and scalable data pipelines. You will collaborate with various stakeholders to ensure the data pipelines are efficient, reliable, and meet the needs of the business.
Key ResponsibilitiesDesign, develop, and maintain data pipelines using Aladdin Data Enterprise Data Platform framework
Develop ETL/ELT data pipelines using Python, SQL and deploy them as containerized apps on a Kubernetes cluster
Develop API for data distribution on top of the standard data model of the Enterprise Data Platform
Design and develop optimized back-end services in Java / Python for APIs to handle faster data retrieval and optimized processing
Develop reusable back-end services for data pipeline processing in Python / Java
Develop data transformation using DBT (Data Build Tool) with SQL or Python
Ensure data quality and integrity through automated testing and validation using tools like Great Expectations
Implement all observability requirements in the data pipeline
Optimize data workflows for performance and scalability
Monitor and troubleshoot data pipeline issues, ensuring timely resolution
Document data engineering processes and best practices whenever required
Must have 5 to 8 years of experience in data engineering, with a focus on building data pipelines and Data Services APIs
Strong server-side programming skills in Python and/or Java.Experience working with backend microservices and APIs using Java and/or Python
Experience with Apache Airflow or any other orchestration framework for data orchestration
Proficiency in DBT for data transformation and modeling
Experience with data quality validation tools like Great Expectations or any other similar tools
Strong at writing SQL and experience with relational databases like SQL Server, PostgreSQL
Experience with cloud-based data warehouse platform like Snowflake
Experience working on NoSQL databases like Elasticsearch and MongoDB
Experience working with container orchestration platform like Kubernetes on AWS and/or Azure cloud environments
Experience on Cloud platforms like AWS and/or Azure
Ability to work collaboratively in a team environment
Need to possess critical skills of being detail oriented, passion to learn new technologies and good analytical and problem-solving skills
Experience with Financial Services application is a plus
Effective communication skills, both written and verbal
Bachelor’s or Master’s degree in computer science, Engineering, or a related field
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.
