Senior Data Architect / Data Engineer, Vice President

Blackrock

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
New York, NY
Salary
$162,000–$215,000 / yr
Posted
31 days ago
Freshness
Confirmed live today
Closes
Oct 31, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $172k
This role $188k
$118k most similar roles pay here $226k

This role pays more than 62% of similar roles. Most pay $128,005–$215,100 — the shaded band above. At the midpoint, this role pays about $188k versus about $172k for comparable roles.

Based on 240 similar postings.

Employer

About Blackrock

BlackRock is the world''s largest asset management firm, providing investment management, risk management, and advisory services to institutional and retail clients through its Aladdin technology platform. Industry: Asset Management & Financial Services

Blackrock currently has 33 open roles on FindRole.

Listed pay typically runs $162,000–$215,000 across 31 roles with salary data.

Most-posted roles

View all roles at Blackrock

At a glance

TL;DR · Senior Data Architect / Data Engineer, Vice President

Senior Data Architect/Data Engineer, Aladdin Engineering - Vice President joins the Post Trade Accounting team to build resilient systems for global post-trade operations. This role involves designing canonical data models from conceptual to physical levels, developing ELT/ETL pipelines in Snowflake and SQL Server, and creating analytics-ready datasets with clear metric definitions. The engineer will implement robust pipeline patterns like incremental processing and idempotency while ensuring data quality through observability practices and performance tuning. Key technologies include Snowflake, SQL Server, Redis, Elasticsearch, Cosmos DB, and programming languages such as Python, Java, or Scala. The role addresses the complex challenge of providing accurate, scalable accounting across global operations by managing high-volume, real-time data through distributed event streaming and messaging platforms. Candidates must possess strong skills in dimensional modeling, schema evolution, and infrastructure-as-code to deliver business-critical capabilities.

What you'll do

  • Design canonical data models ranging from conceptual to physical levels to power reporting and downstream integrations.
  • Build and maintain analytics-ready datasets in Snowflake with clear metric definitions for consistent enterprise reporting.
  • Develop reliable ELT/ETL pipelines across Snowflake and SQL Server for batch and low-latency data ingestion.
  • Implement robust pipeline patterns including incremental processing, idempotency, deduplication, and backfill strategies.
  • Establish and enforce data quality and observability practices such as freshness checks, alerting, and runbooks.
  • Optimize analytical performance and costs by applying Snowflake best practices and SQL Server performance tuning.
  • Publish curated data to downstream systems like Elasticsearch and Cosmos DB using defined contracts and monitoring.
  • Manage documentation, lineage, schema evolution, and secure handling of sensitive PII data.

What we're looking for

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
  • 8+ years of experience building production data systems with ownership of data modeling and pipeline engineering.
  • Advanced SQL skills including query planning, performance tuning, and hands-on experience with Snowflake or Microsoft SQL Server.
  • Proven experience in analytical data modeling using dimensional modeling, star schemas, and conformed dimensions.
  • Hands-on experience designing and implementing ELT/ETL pipelines for both batch and near-real-time processing.
  • Proficiency in at least one general-purpose language such as Python, Java, or Scala for automation and orchestration.
  • Working knowledge of modern data engineering practices including testing, CI/CD, environment promotion, and monitoring.
  • Experience with dbt, orchestration tools (Dagster, Prefect), streaming platforms, or cloud-native infrastructure (preferred).

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