This listing doesn't post a salary. Most similar roles pay
$129,449–$211,200.
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
81 open roles
on FindRole.
Listed pay typically runs
$147,500–$195,000
across 77 roles with salary data.
Associate Data Engineer, Data Management – Data Office joins the BlackRock Data Office to build and advance enterprise data capabilities through trusted, scalable, and governed products. This role involves designing, developing, and maintaining high-performance data pipelines for batch and real-time ingestion, transformation, and publishing from diverse sources like CSV, Excel, and APIs. The engineer will develop reusable frameworks, automate manual processes, and ensure data quality, security, and lineage across the platform. Key technologies include Python, Java, Scala, SQL, Snowflake, Databricks, and Great Expectations. Candidates must navigate complex distributed systems using tools such as dbt, Spark, and various CI/CD platforms like Jenkins or Azure DevOps. The role addresses critical challenges in data governance and infrastructure to support analytics, reporting, machine learning, and artificial intelligence within a large-scale enterprise environment.
What does a Data Engineer earn?
Median $183138 from 214 postings across 58 companies.
Design, develop, and maintain scalable, high-performance data pipelines to support enterprise products.
Build and optimize batch and real-time data ingestion, transformation, and publishing processes from diverse sources.
Create reusable data engineering frameworks and automation to improve platform efficiency and developer productivity.
Ensure all data products meet corporate standards for quality, security, governance, lineage, and observability.
Troubleshoot complex production issues and perform root cause analysis to implement sustainable solutions.
Contribute to engineering standards, including code reviews, testing practices, and CI/CD automation.
Automate manual ingestion processes while optimizing data delivery according to service-level agreements.
Identify opportunities for performance tuning, scalability improvements, and cost optimization across the data platform.
What we're looking for
Associate level requires 3–6 years of experience in software engineering, data engineering, or related technical disciplines.
Requires 4+ years of programming experience in Python, Java, or Scala, including UDFs and automated testing with frameworks like pytest.
Requires 4+ years of experience building large-scale data pipelines using dbt, distributed event streaming, and DAG-based workflow orchestration.
Requires 4+ years of experience developing production workloads on distributed data analytics engines with a focus on performance tuning and optimization.
Requires 4+ years of experience using SQL-based analytics layers, including partitioning, bucketing, and various data serialization formats.
Requires 4+ years of experience with Transact-SQL, relational/non-relational databases, and GraphQL.
Requires strong proficiency in Snowflake, Databricks, and tools for data quality such as Great Expectations.
Requires experience with cloud environments (AWS, Azure), containerization (OCI, Kubernetes), CI/CD pipelines, and RESTful API design via Swagger/OpenAPI.
Python
Oracle SQL
Cassandra
Linux
Git
Data Pipelines
MLOps
Machine Learning
Data Architecture
SQL
NoSQL
Data Visualization
Business Intelligence
STDF
Software Engineering
Data Engineering