Lead Data Quality Engineer

About this role

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 EDP team is responsible for the data ecosystem within BlackRock with a mission to build a centrally managed unified platform that takes care off end-to-end firm wide data needs. 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 quality 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 Data Quality Audit 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 and implement the technology solution 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 Data Quality Audit Framework 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.

The role would be responsible for building and providing adequate technical solutions and capabilities to deliver business usable data. There is already a framework in place to deliver Technical Data Quality and Business Data Quality capabilities using custom Python and open sources Great Expectations to confirm to data standards across Timeliness, Uniqueness, Completeness, Accuracy, Consistency and Validity. The DQ tasks are orchestrated in the data pipeline leveraging Apache Airflow.

Responsibilities:

Lead data engineer is expected to be engaged from inception of projects, understand requirements, design architecture, develop, deploy, and maintain data quality framework within Data Governance & Operation Engineering team. The goal is to provide a robust and scalable data quality framework that can take care of all kinds of data quality assessment needs and be able to surface the full telemetry and outcomes to Data Operations and Stewards team. The team needs to help increase the automation of Data Quality validations. support both internal and external teams to leverage the reusable data pipeline components and adopt to the standards of modern data platform while constantly working towards enhancing the enabling core frameworks with new features and improving platform performance and scalability.

• Guide & Contribute to the development life cycle and maintain DQ Audit framework, collaborate with data acquisition and pipeline framework (Near Real Time Use cases, Azure Data Storage, S# etc.), 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 within and outside the team.
• Lead the build of highly complex DQ frameworks for various 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 8+ years’ experience as a data engineer
• Experience with object-oriented design patterns
• Experience with Great Expectations data quality assessment framework
• Experience in SQL, PL/SQL programming, Stored procedures, UDFs
• Experience in core Python / PySpark for application development
• 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:

• Data Quality Framework design and Workflow Orchestrations
• Experience with Snowflake, SnowPipe, Snowpark
• Exposure with Workflow management tools such as Apache 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.

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.