Senior Data Architect/Data Engineer, Aladdin Engineering - Vice President

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 Kafka 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 → logical → 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., Airflow, Dagster, Prefect) and patterns for dependency management and backfills.
• Streaming and event-driven data experience (e.g., Kafka, 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 (Docker/Kubernetes, 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 -