Data Engineer (Databricks), Assistant Vice President

State Street•Boston, MA

1d•$110,000 - $177,500

About The Position

We are seeking a Data Engineer to design, build, and support a modern Legal Data Lakehouse platform on AWS and Databricks. This role will focus on developing scalable, high‑performance data pipelines and enabling trusted, governed data capabilities supporting legal operations, compliance analytics, reporting, and AI/ML use cases. The ideal candidate brings strong hands-on experience in Databricks, AWS data platforms, and enterprise data engineering practices, with experience delivering solutions in regulated environments aligned to security, compliance, and audit requirements. State Street's Legal, Security, and Compliance functions operate across contracts, matters, regulatory obligations, documents, and workflows distributed across multiple systems. Building robust data pipelines ensures data is accessible, reliable, and usable for analytics and decision-making. This role is critical to enabling a scalable and governed data foundation supporting legal analytics and operational reporting while strengthening data quality, auditability, and consistency.

Requirements

8+ years of experience in Data Engineering or data platform development
Strong hands-on experience with Databricks and Apache Spark
Proficiency in PySpark, Python, and SQL
Experience with AWS data platform services, including: S3, Glue, Lambda, IAM
Experience working with Delta Lake and lakehouse architecture
Solid understanding of: Distributed data processing, ETL/ELT frameworks, Data modeling techniques

Nice To Haves

Hands-on experience with Databricks platform components (Delta Lake, Workflows, Unity Catalog)
Strong experience building end-to-end data pipelines (batch and streaming) using AWS and Databricks
Familiarity with performance optimization techniques in Spark and Delta Lake
Experience supporting analytics, reporting, or AI/ML use cases on a lakehouse platform
Understanding of data governance, metadata management, and security controls
Experience in Legal, Compliance, Financial Services, or regulated industries
Understanding of legal data constructs such as contracts, clauses, obligations, and matters
Exposure to unstructured data processing or document/NLP pipelines
Experience with Power BI, Power Apps, or Power Platform
Experience handling sensitive data in audit-driven environments

Responsibilities

Design, build, and maintain scalable data pipelines using PySpark, Python, and Spark SQL
Develop and optimize ETL/ELT workflows on Databricks using Delta Lake
Implement Lakehouse architecture (Bronze/Silver/Gold layers) for enterprise data platforms
Build and manage Databricks Jobs, Workflows, and Notebooks for batch and streaming workloads
Develop reusable frameworks for data ingestion, processing, and orchestration
Containerize data workloads using Docker and automate processes via scripting
Integrate Databricks data pipelines with Power Platform solutions (Power Apps, Power Automate)
Enable data exposure for business users via APIs, connectors, and curated datasets
Design and optimize data lakehouse architectures using Databricks
Integrate data from SQL Server, Oracle, and other enterprise source systems
Apply advanced data modeling techniques (dimensional modeling, partitioning, optimization)
Work with structured and semi-structured data (e.g., JSON, Parquet)
Tune performance using caching, indexing, and Spark optimization techniques
Publish curated datasets for consumption in Power BI dashboards/ Power Apps / Power Automate workflows
Ensure data quality using unit testing, validation frameworks, and automated checks
Monitor and troubleshoot distributed Spark workloads and pipelines
Analyze logs and resolve production issues across Databricks and cloud environments
Maintain data lineage, consistency, and audit readiness
Collaborate with Legal, Security, Compliance, and Enterprise Data teams to deliver scalable solutions
Translate business requirements into robust data engineering designs
Act as a Subject Matter Expert (SME) in Databricks and Lakehouse architecture
Lead initiatives with minimal supervision and take full ownership of deliverables
Support implementation of data governance frameworks using Databricks Unity Catalog and AWS controls (IAM, KMS)
Ensure adherence to: Data privacy and regulatory requirements (e.g., GDPR), Internal security and audit standards
Implement and maintain: Data access controls, Data classification and handling standards
Collaborate with IAM and security teams to ensure secure data access
Design and maintain CI/CD pipelines using Harness, Azure DevOps, or GitHub
Automate deployment of Databricks assets using Databricks Repos and CLI
Monitor, schedule, and optimize workflows using Databricks orchestration tools
Maintain clear documentation including architecture, data flows, and runbooks
Continuously improve performance, scalability, and cost efficiency

Benefits

our retirement savings plan (401K) with company match
insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages
paid-time off including vacation, sick leave, short term disability, and family care responsibilities
access to our Employee Assistance Program
incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans)
eligibility for certain tax advantaged savings plans
inclusive development opportunities
flexible work-life support
paid volunteer days
vibrant employee networks