About this role
About this Role:At BlackRock, technology is the foundation of our business. As a Data Engineer, you'll build resilient systems that power our global post-trade operations. You'll design and deliver enterprise-scale software with a focus on reliability, performance, and clean engineering practices.
This role is ideal for engineers who like to innovate and solve complex challenges while fostering a culture of excellence and continuous improvement.
About Post Trade Accounting (PTA):
A major strategic area within Aladdin and one of BlackRock's largest engineering investments.
Responsible for the systems that ensure accurate, scalable, and efficient accounting across global operations.
Expanding into data analytics and pipeline initiatives using Snowflake, Redis, and distributed event streaming and messaging platforms to manage high-volume, real-time data.
Collaborates closely with Product, Operations, and other Engineering teams to deliver business-critical capabilities.
Agile and collaborative environment that values technical depth, quality, and innovation.
Key Responsibilities:
Partner with domain experts, product, and engineering teams to design canonical data models (conceptual 12 logical 12 physical) that power trusted reporting, analytics, and downstream integrations.
Build and evolve analytics-ready datasets in Snowflake (curated layers / data marts), including clear metric definitions (grain, dimensions, measures) that enable consistent enterprise reporting.
Design and develop reliable ELT/ETL pipelines across Snowflake and SQL Server to support both scheduled batch loads and low-latency ingestion where needed.
Implement robust pipeline patterns such as incremental processing, idempotency (replay-safe loads), deduplication, and backfill/reprocessing strategies.
Establish and enforce data quality and observability practices (freshness, completeness, accuracy checks; alerting; runbooks; SLAs) to keep data products production-grade.
Optimize analytical performance and cost by applying Snowflake best practices (clustering/partition strategies, materializations, query optimization) and SQL Server performance tuning where appropriate.
Publish curated data to downstream systems and serving layers when needed (e.g., search indices like Elasticsearch and operational stores like Cosmos DB) with clear contracts and monitoring.
Drive best practices for documentation, lineage, schema evolution, and secure handling of sensitive data (PII) in collaboration with platform and governance partners.
Qualifications / Competencies:
B.S./M.S. in Computer Science, Engineering, or related discipline (or equivalent practical experience).
8+ years of experience building production data systems, with demonstrated ownership of data modeling and data pipeline engineering.
Strong SQL skills (advanced querying, query plans, performance tuning) with hands-on experience in Snowflake and/or Microsoft SQL Server.
Proven experience with data modeling for analytics (dimensional modeling / star schemas, conformed dimensions, slowly changing dimensions) and translating business concepts into robust schemas.
Hands-on experience designing and implementing ELT/ETL pipelines, including batch and near-real-time patterns.
Proficiency in at least one general-purpose language used for data engineering (e.g., Python, Java, or Scala) for automation, orchestration, and integrations.
Working knowledge of modern data engineering practices: testing for transformations, CI/CD, environment promotion, and operational monitoring.
Strong communication skills and comfort collaborating with domain experts to turn ambiguity into clear, implementable data products.
Nice to Have:
Experience with transformation and modeling frameworks (e.g., dbt) and/or a semantic/metrics layer approach.
Exposure to orchestration tools (e.g., Directed acyclic graph-based workflow orchestration framework for data and batch processing, Dagster, Prefect) and patterns for dependency management and backfills.
Streaming and event-driven data experience (e.g., distributed event streaming and messaging platforms, CDC patterns) and understanding of late-arriving data, watermarking, and replay.
Experience integrating downstream serving/search systems (e.g., Elasticsearch) and operational datastores (e.g., Cosmos DB).
Familiarity with data governance and observability tooling (catalog/lineage, OpenLineage-style concepts, data quality frameworks).
Cloud-native exposure (Open Container Initiative (OCI) container image packaging and runtime/Enterprise-grade container orchestration platform supporting declarative infrastructure and horizontal scaling, AWS/Azure/GCP) and infrastructure-as-code (Terraform).
Interest in financial systems, accounting, or investment technology.For New York, NY Only the salary range for this position is USD$162,000.00 - USD$215,000.00 . 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.
