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About this role

When BlackRock started in 1988, its founders envisioned a company that combined the best of financial services with cutting edge technology. They imagined a business that would provide financial services to clients as well as technology services to other financial firms. The result of their vision is Aladdin, our industry leading, end-to-end investment management platform. With assets valued over USD $7 trillion managed on Aladdin, our technology empowers millions of investors to save for retirement, pay for college, buy a home and improve their financial wellbeing.

About Data Ops Engineering (DOE)

Data is at the heart of Aladdin and increasingly the ability to consume, store, analyse and gain insight from data has become a key component of our competitive advantage. The DOE team is responsible for the data ecosystem within BlackRock. Our goal is to build and maintain a leading-edge data platform that provides highly available, consistent data of the highest quality for all users of the platform, notably investors, operations teams, and data scientists. We focus on evolving our platform to deliver exponential scale to the firm, powering the future growth of Aladdin data.

About this role

As a lead data engineer at BlackRock, you will get an experience working at one of the most recognized financial companies in the world while being part of a team responsible for building ETL framework for next generation Enterprise Data platform (EDP), which is designed to automate data acquisition, ingestion, transformation, and distribution processes to handle enterprise-wide data processing capabilities. You will partner with data and analytics experts to deliver high quality data analytical solutions to our consumers.

It is important to have a long track-record of delivering high-quality products frequently and repeatably. This role is expected to lead the design of highly complex and/or sensitive components. Also responsible for leveraging to the firm's broader technology strategy to make technology decisions.

Lead data engineers are expected to work in the areas of building frameworks for ETL/ELT use cases and metadata driven data pipeline processing engines with cloud native service knowledge are ideal candidates. We are looking for the candidates, who like to innovate and resolve complex data problems.

Responsibilities:

Lead data engineer is expected to be engaged from inception of projects, understand requirements, design architecture, develop, deploy, and maintain ETL / ELT framework. The goal is to increase the automation of data pipelines, support both internal and external teams to leverage the reusable ETL components and adopt to the standards of modern data platform while constantly working towards enhancing the enabling core ETL framework with new features and improving platform performance and scalability.

• Guide & Contribute to the development life cycle and maintain ETL framework, acquisition framework, workflow orchestration for data pipelines, including participation in tactical projects and strategic programs.

• Participate in brainstorming sessions to generate ideas for designing and building data engineering solutions using standard frameworks. Provide ideas for process enhancements that will result in cycle time reductions.

• Explore new tools and technologies to enhance the capabilities for the frameworks.

• Work closely with program managers, product teams and data stewards throughout the SDLC cycle.

• Guide development team conduct end-to-end tests to ensure production operations run successfully after every release cycle.

• Provide L2 or L3 support for technical and/or operational issues.

• Provide technical expertise to the development teams and establish strong bonds with technologists outside the team.

• Ability to coordinate and collaborate with engineers outside the team.

• Lead the build of highly complex ETL/ELT components. Adhere to the firm's technology strategy with best practices.

• Take ownership of multiple large components and/or initiatives requiring coordination and cooperation with others.

• Identify communication needs and ensure smooth flow of information within the organization.

• Participate in technology initiatives outside the direct team purview.

Required Experience:

• At least 5+ years’ experience as a data engineer

• ETL/ELT Framework design and Workflow Orchestrations

• Experience with object-oriented design patterns

• Experience with ETL Performance Tuning

• Experience in SQL, PL/SQL programming, Stored procedures, UDFs

• Experience in Python / PySpark programming

• Experience with Agile development concepts and related tools

• Experience conducting root cause analysis and solve issues.

• Excellent written and verbal communication skills.

• Ability to operate in a fast-paced environment.

• Strong interpersonal skills with a can-do attitude under challenging circumstances

• BS equivalent degree

Desired Qualifications:

• Experience with Snowflake, SnowPipe, Snowpark

• Exposure with Workflow management tools such as Airflow

• ETL tools like DBT

• Experience in Azure Cloud Native services

• Exposure to real time streaming platforms such as SnowPipe Streaming, Kafka

• Bachelor’s degree in computer science is preferred.

For New York City only: The salary range for this position is $214,500 - $157,500. Additionally, employees are eligible for an annual discretionary bonus, and benefits including heath care, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.

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 (http://careers.blackrock.com/) | Twitter: @blackrock (https://twitter.com/blackrock) | LinkedIn: www.linkedin.com/company/blackrock

BlackRock is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.

BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.