Associate
$147.5kBlackRock
About this role
Company: BlackRock Financial Management, Inc.
Job Title: Associate
Location: 1 University Square Drive Princeton, NJ 08540
Job Duties: Drive the architectural design, development, and implementation of mission-critical enterprise big data operational platforms and data migration initiatives. Leverage cloud-native solutions to enable advanced data analysis and generative AI outcomes, driving optimization across the investment product sales lifecycle. Architect and execute comprehensive end-to-end platform migration strategies for legacy Apache Hadoop/Apache Hive distributed data processing systems to modern cloud-native architectures utilizing Databricks Lakehouse Platform, Apache Airflow orchestration, and Snowflake cloud data warehouse. Design and implement comprehensive self-service data pipeline frameworks having complex data transformation logic converting MapReduce paradigms and Hive Query Language (HiveQL) operations to Apache Spark 3.x DataFrame API and PySpark distributed computing frameworks. Develop automated, event-driven and optimized Apache Airflow Directed Acyclic Graph (DAG) workflows supporting diverse data ingestion and transformation of structured and semi-structured formats. Integrating comprehensive data quality validation python frameworks (Great Expectations) with automated checks for completeness, accuracy, consistency, uniqueness, timeliness, and validity constraints through configurable business rules. Develop complex data transformation models leveraging Data Build Tool (DBT) python frameworks to ensure scale and efficient data outcomes with lineage. Design and implement RESTful API endpoints utilizing Swagger and OpenAPI specifications developing backend services that accept CSV, XML, JSON, and Microsoft Excel file uploads with intelligent parsing algorithms transforming diverse formats into standardized JSON representations. Configure ingestion schedules and monitor pipeline execution status via telemetry frameworks. Engineer and optimize a scalable Snowflake ecosystem by implementing sophisticated data modeling, rigorous security controls, and advanced performance tuning, while pioneering the use of advanced AI and data product capabilities using Snowflake Cortex, Snowpark, vectorized storage, and machine-learning features. Build and manage high-performance ETL and ELT pipelines using Delta Live Tables (DLT), leveraging its native automation for orchestration, data transformation, and quality validation. Managing Databricks notebooks and job configurations as code through Git integration, ensuring stable production deployments. Partner with data scientists, business analysts, product managers, and executive stakeholders to translate complex business requirements into technical data platform capabilities, conduct technical design reviews, architecture discussions, and knowledge transfer sessions with engineering teams, provide production support for data pipeline failures performing root cause analysis and implementing preventive measures, participate in agile development ceremonies.
Qualifications: Bachelor’s degree in Computer Science, Engineering or a related field and two (2) years of experience in the job offered or as Data Engineer, or a related role. Must have two (2) years of experience with: Python and Scala programming skills in Core Python and PySpark, including creating and supporting UDFs and modules including PyTest; Building and optimizing Big Data pipelines, architectures and data sets using Hadoop, Spark and HIVE; Data pipeline and workflow management tools including Airflow and DBT Kafka; Developing on Spark in a production environment including parallel execution, deciding resources and different modes of executing jobs; Using Hive, Yarn and Sqoop for bucketing, portioning, tuning and handling different file formats including ORC, PARQUET and AVRO; Transact SQL, No-SQL and GraphQL; Snowflake and Pandas; Deployment, maintenance and administrative tasks related to Cloud, OpenStack, Docker, Kafka and Kubernetes; Cloud technologies including Azure and AWS; Databricks; JSON, XML and Unstructured data; and Open API and Swagger.
Salary: $147,500 – 148,000
To apply, please click “Apply” on this webpage.
For Princeton, NJ Only the salary range for this position is USD$0.00 - USD$0.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, 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.
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 workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC’s Know Your Rights poster and its supplement and the pay transparency statement.
BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email View email address on aiapply.co. All requests are treated in line with our privacy policy .
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