We are seeking an Analytics‑focused Data Engineer to design and build trusted, analytics‑ready datasets on a modern AWS and Databricks data platform. This role is critical to enabling business intelligence, reporting, and advanced analytics by transforming raw data into well‑modeled, high‑quality, and performant analytics layers.

You will work closely with analytics, BI, finance, and product teams to ensure data is easy to consume, well understood, and reliable for decision‑making at scale.

Key Responsibilities:

Analytics‑Ready Data Modeling

• Design and implement analytics‑optimized data models (fact/dimension, star/snowflake schemas).
• Build and maintain curated analytics layers (gold tables) in Databricks using Delta Lake.
• Translate business requirements into clear, reusable datasets for dashboards and reports.
• Support semantic consistency across metrics, dimensions, and KPIs.

Data Pipelines & Transformations:

• Develop and maintain ETL/ELT pipelines using Databricks (Spark SQL, Py Spark).
• Transform raw and intermediate data into clean, documented, and performant analytics datasets.
• Implement incremental processing, partitioning, and optimization techniques for BI workloads.
• Ensure pipelines are resilient, observable, and production‑ready.

AWS Analytics Platform:

• Leverage AWS services such as S3, Glue, Redshift, Lambda, and IAM to support analytics use cases.
• Integrate Databricks with AWS storage and security services.
• Monitor pipeline execution, performance, and cost for analytics workloads.

Data Quality, Metrics & Trust

• Implement data quality checks, reconciliation logic, and anomaly detection for analytics data.
• Validate accuracy of business metrics used in executive dashboards and reports.
• Support data lineage, documentation, and metric definitions.
• Partner with stakeholders to ensure a single source of truth for analytics.

BI & Analytics Enablement:

• Support downstream tools such as Power BI, Tableau, or similar BI tools.
• Optimize datasets for dashboard performance and concurrency.
• Collaborate with analysts to improve query patterns and data usage.
• Enable self‑service analytics through well‑designed datasets and documentation.

Required Qualifications:

• 5–8+ years of experience in data engineering or analytics engineering roles.
• Strong experience with Databricks for analytics workloads.
• Advanced proficiency in SQL (complex transformations, window functions, performance tuning).
• Solid experience with AWS‑based analytics architectures.
• Strong experience with data modeling for analytics.
• Proficiency in Python or Py Spark.
• Experience supporting BI, reporting, and analytics teams.

Nice to Have:

• Experience with Analytics Engineering / ELT patterns.
• Familiarity with dbt or similar transformation frameworks.
• Experience supporting finance or executive reporting.
• Knowledge of data governance, metric catalogs, or data discovery tools.
• Experience with streaming data for near‑real‑time analytics.
• Exposure to regulated or enterprise analytics environments.

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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