Data Engineer, Officer - State Street Investment Management
Who we are looking forState Street Investment Management’s Data, Analytics & AI Services (DAAIS) team is looking for a Data Engineer - Officer to be part of the architecture, engineering execution, modernization strategy, and technology roadmap supporting the investment management business. The successful candidate will bring hands-on development expertise in large-scale data platform architecture, distributed computing, data pipeline engineering, and modern cloud architecture.Why this role is important to usThe team you will be joining is a part of State Street Investment Management, one of the largest asset managers in the world. We partner with many of the world’s largest, most sophisticated investors and financial intermediaries to help them reach their goals through a rigorous, research-driven investment process. With over four decades of experience and trillions of dollars in assets under management, we offer one of the broadest selections of services across asset classes, risk profiles, regions and styles. As pioneers in index, ETF, and ESG investing, we are always inventing new ways to invest.Join us if making your mark in the asset management industry from day one is a challenge you are up for.What you will be responsible forThese skills will help you succeed in this roleDesign, develop, test, and maintain data pipelines using Python, PySpark, and SQL.Design, build, and manage robust workflows and data ingestion, transformation solutions using Databricks and SnowflakeHands-on experience with Databricks, Snowflake on AWS (Azure acceptable)Design and maintain CI/CD pipelines using tools such as Jenkins, Artifactory, GitHub.Develop containerized applications for APIs, event based, streaming and batch using Docker.Prior experience on working in Agile project management practicesWork under minimal supervision to analyze, design, develop, test, and debugParticipate in cross-team group activities to complete assignments.Work with cross-functional teams and other engineers on the core platform capabilitiesDevelop Iceberg, unity catalog based tables for consistent, performant analytical access across multiple compute engines.Partner with product owners, analytics teams, and downstream consumers to translate business requirements into technical solutionsApply AI code generation tools (e.g., Anthropic Code, Codex, and GitHub Copilot) to accelerate development, improve quality, and increase productivity.Excellent verbal and written communication and should be able to work with all the stakeholders.Required QualificationsMaster’s degree in Computer Science or a related engineering discipline.6-10 years of technology experience with Data Engineeting focusStrong hands-on in Python, Spark, SQL, Databricks and Snowflake, with the ability to design, debug, and optimize distributed data processing;Experience building Lakehouse platforms using Snowflake and Databricks on AWS (Azure acceptable), supporting high concurrency analytical workloads.Profici...