Senior Data Engineer - Manager at State Street

Job Description:

We are currently seeking a Data Engineer to help us collect, transform and extract meaning from data for the Global Technology Services (GTS) Control Tower team at State Street. The position performs a wide range of activities with experts from GTS, business intelligence, business analysis, data engineering, process engineering, governance, and data analysts to collaboratively solve a wide array of complex technical problems.

About the GTS Control Tower team:

Our technology function, Global Technology Services (GTS), is vital to State Street and is the key enabler for our business to deliver data and insights to our clients. We’re driving the company’s digital transformation and expanding business capabilities using industry best practices and advanced technologies such as cloud, artificial intelligence and robotics process automation.

We offer a collaborative environment where technology skills and innovation are valued in a global organization. We’re looking for top technical talent to join our team and deliver creative technology solutions that help us become an end-to-end, next-generation financial services company.

Join us if you want to grow your technical skills, solve real problems and make your mark on our industry.

The GTS Control Tower team is an exciting and growing area of State Street with unique insight into the whole spectrum of our data, metrics, and dashboards at State Street. This name change reflects the work we are actively doing across GTS: integrating dependency management, business analysis, process design, and governance to transform data into action and keep remediation efforts flying smoothly.

The GTS Control Tower Mission:

Our core focus is on transforming data into actionable insights. Our goal is to enable GTS Leadership to accelerate progress against key strategic initiatives across GTS and to drive results.

Core Responsibilities: Data Integration & Ingestion

• Design, build, and maintain scalable data pipelines to ingest data from diverse sources including relational databases (SQL Server, Azure SQL), cloud platforms, files (Excel/CSV), and enterprise systems.
• Leverage Microsoft Fabric (Data Factory, Lakehouse, Warehouses) and Azure Data Factory to ensure reliable, secure, and well-structured data ingestion.

Data Transformation & Modeling:

• Develop and optimize ETL/ELT workflows using Databricks (PySpark, Spark SQL) and Microsoft Fabric (Python, Py Spark, T‑SQL).
• Implement medallion architecture (Bronze, Silver, Gold) to support scalable and governed analytics.
• Design and maintain Lakehouse and data warehouse models, including dimensional (star/snowflake) schemas for downstream analytics and reporting.
• Collaborate with analytics and Power BI teams to support semantic models and DAX measures where required.

Performance & Reliability:

• Optimize Spark jobs, SQL queries, and data models for performance, scalability, and cost efficiency.
• Monitor data pipelines and proactively resolve data quality, performance, and reliability issues.

Data Governance & Documentation:

• Create and maintain comprehensive documentation for data pipelines, transformation logic, data models, and operational runbooks.
• Adhere to enterprise data standards, security, and compliance requirements to ensure long‑term maintainability and transparency**.What We Value:**
• A strong willingness to learn, adapt, and continuously improve in a fast‑evolving data ecosystem.
• Ownership mindset with a focus on delivering high‑quality, measurable outcomes.
• Analytical thinking and problem‑solving skills with the ability to propose innovative and scalable solutions.
• Collaboration and effective communication within cross‑functional teams.

Requirements:

• Strong hands-on experience with SQL and data engineering concepts.
• Advanced working knowledge of Databricks (PySpark, Spark SQL) and/or Microsoft Fabric.
• Experience building and maintaining production‑grade data pipelines and data models.
• An online portfolio or repository (using non‑confidential data) that demonstrates data engineering and analytics skills.

Preferred Qualifications

• Microsoft Certifications for any of the following: Fabric Data Engineer Associate (DP-700), Databricks Data Engineer Associate
• Prior experience with Microsoft Fabric, Databricks, and cloud data platforms ; Relational and non‑relational databases ; Data pipelines, medallion architecture, and dimensional modeling
• 9+ years of experience in data management or equivalent roles delivering large‑scale, complex data and analytics solutions focusing on technology transformation, big data, automation, and business intelligence.
• Exposure to data visualization and supporting analytical workloads with a strong focus on usability and performance.

Are you the right candidate? Yes!

We truly believe in the power that comes from the diverse backgrounds and experiences our employees bring with them. Although each vacancy details what we are looking for, we don’t necessarily need you to fulfil all of them when applying. If you like change and innovation, seek to see the bigger picture, make data driven decisions and are a good team player, you could be a great fit.

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

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