Associate - Data Engineering

BlackRock•Atlanta, GA

16h•Hybrid

About The Position

As an Associate on the Enterprise Data Platform team, you will be part of a team responsible for building and modernizing the core framework of BlackRock’s next-generation enterprise data platform. This platform is designed to automate and standardize data acquisition, ingestion, transformation, orchestration, and distribution at enterprise scale. This is a hands-on engineering role for a strong software developer with experience in Python and backend API development, along with exposure to data platforms and workflow-driven systems. The role sits at the intersection of data platform engineering and backend platform development. You will help build and enhance modular, API-driven platform capabilities that make core services easier to access, operate, and scale. A key focus of this role is designing and developing internal platform services and APIs that expose capabilities such as metadata, logging, orchestration, workflow generation, onboarding, and operational control. These services will support more flexible and standardized interaction patterns across the platform, including internal tools, automation, scripts, UIs, and AI-enabled workflows. You will work closely with senior engineers, product partners, and platform teams to deliver scalable, reliable, and maintainable solutions that advance the firm’s enterprise data capabilities. The ideal candidate brings strong Python engineering skills, practical experience building backend services and APIs, and an interest in applying those skills within a modern data platform environment.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a related field.
3+ years of experience in software engineering, backend engineering, data engineering, or data platform engineering roles.
Strong hands-on programming experience in Python.
Strong SQL skills and experience working with relational or analytical data platforms.
Experience designing and developing backend services and APIs using REST-based frameworks such as FastAPI or Flask.
Experience with gRPC and Protocol Buffers, or other contract-first API development patterns.
Experience designing APIs that interact with orchestration systems, cloud storage, metadata services, or platform-control functions.
Experience building scalable, maintainable solutions in cloud-native or distributed environments.
Working experience with containers and Kubernetes-based deployment environments.
Experience with at least one major cloud platform; Azure experience is strongly preferred.
Strong understanding of object-oriented design, software engineering best practices, and production-grade development practices.
Strong communication and collaboration skills, with the ability to work effectively across engineering and non-engineering partners.
Ability to operate effectively in a fast-paced environment and take ownership of assigned deliverables.

Nice To Haves

Experience with Apache Airflow or comparable workflow orchestration technologies.
Experience with Snowflake and related cloud data warehouse capabilities.
Experience with dbt or similar transformation frameworks.
Exposure to enterprise data platforms, ETL/ELT workflows, or reusable data framework components.
Experience with real-time, event-driven, or message-based platforms and technologies such as Kafka or streaming ingestion patterns.
Familiarity with authentication, authorization, and related API security concepts.
Experience integrating AI/ML or LLM-based services into enterprise platforms, developer workflows, or operational processes.
Understanding of prompt engineering, model evaluation, or responsible AI practices.
Exposure to Java or experience working in mixed Python/Java enterprise environments.

Responsibilities

Design, develop, and maintain scalable platform services and APIs that support metadata, logging, orchestration, workflow generation, onboarding, and other core enterprise data platform capabilities.
Build backend components and service interfaces that help evolve the platform toward a more modular, API-driven architecture.
Contribute to the development and enhancement of shared platform components used across enterprise data workflows.
Participate across the full software development lifecycle, including requirements analysis, design, development, testing, deployment, and ongoing enhancement.
Develop backend services using Python-based frameworks such as FastAPI or Flask, and contribute to contract-first API development using gRPC and Protocol Buffers.
Partner with senior engineers and cross-functional teams to translate business and operational requirements into robust technical solutions.
Improve performance, scalability, resilience, and observability across platform services and data workflows.
Contribute to engineering standards, API conventions, code quality, and development best practices.
Support the integration of AI-enabled capabilities and external AI services into platform workflows where they improve automation, quality, or developer productivity.