Data Engineer (Databricks), Assistant Vice President
AI in this role
Data Engineer (Databricks), Assistant Vice President
Corporate Functions Technology (Legal & Security)
Who We Are Looking For
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.
Why This Role Is Important to Us
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.
What You Will Be Responsible For
Software Development
- 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
Data Platform & Database Management
- 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
Testing & Troubleshooting
- 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
Ownership & Collaboration
- 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
Governance, Security & Compliance
- 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
Delivery & Documentation
- 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
What We Value
The skills that will help you succeed in this role include:
- Strong analytical thinking and problem-solving skills
- Hands-on expertise in data engineering and distributed data processing
- Ability to work in a fast-paced, enterprise environment
- Effective communication and collaboration with cross-functional teams
- Ownership mindset with focus on quality, scalability, and performance
Education & Preferred Qualifications
Education
- Bachelor's or Master's degree in computer science, Data Engineering, Information Systems, or a related technical discipline
Required Qualifications
- 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
Preferred Qualifications (Core – Databricks, AWS, Data Lakehouse)
- 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
Nice to Have (Domain & Industry Experience)
- 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
Salary Range:
$100,000 - $167,500 AnnualThe range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.
Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: 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); and, eligibility for certain tax advantaged savings plans.
For a full overview, visit https://hrportal.ehr.com/statestreet/Home.
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.
Discover more information on jobs at StateStreet.com/careers
Read our CEO Statement
Job Application Disclosure:
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
How we rate this
Data Engineer (Databricks), Assistant Vice President at State Street rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Walk me through how you've used Databricks in your day-to-day work.
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: NLP and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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