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Senior Data Platform Architect (Snowflake, Databricks, Open Platforms & Data Virtualization), VP I - State Street Investment Management

Boston, Massachusetts

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Pay
$120,000–202,500/year — pay source
Salary Range: $120,000 - $202,500 Annual The 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.
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What you’ll work on

Full posting
  • Design and Build monitoring as well as chargeback models for billing back to application teams.

  • Lead Iceberg/Horizon/Unity Catalog interoperability across AWS, Azure, and GCP

  • Lead architecture and solutioning for batch applications migrating from legacy platforms (Oracle, mainframe, Unix/Linux ETL, file‑based workflows) to Snowflake/Databricks

From the employer’s posting
The person in this role will ensure the modern platform meets financial‑services regulatory expectations, enterprise security standards (GCS/IAM), and data protection requirements (NPPI/PII). They Will Enable scalable, interoperable delivery across Investment Management use cases. This role is hands‑on, decision‑critical, and risk‑bearing, with accountability for architectural choices that directly impact regulatory compliance, audit defensibility, and business continuity. Platform Designs must be Secure, Scalable, include Disaster Recovery, as well as Data Sharing capabilities. Design and Build monitoring as well as chargeback models for billing back to application teams. Core Responsibilities
Contribute Designs, Patterns, Assets to SSIM Center of Excellence which establishes Best Practices for each platform as well as use cases for Reuse. Lead Iceberg/Horizon/Unity Catalog interoperability across AWS, Azure, and GCP 2. Open Platforms & Open Table Formats
4. Batch Application Solutioning & Modernization Lead architecture and solutioning for batch applications migrating from legacy platforms (Oracle, mainframe, Unix/Linux ETL, file‑based workflows) to Snowflake/Databricks Define patterns for:- Batch ingestion and orchestration (Airflow, Databricks Workflows, Snowflake Tasks/Streams, Control‑M integration)

Tools in this posting

  • Java
  • JavaScript
  • Python
  • Scala
  • SQL
  • AWS
  • Azure
  • Databricks
  • Delta
  • Google Cloud (GCP)
  • Google Cloud Storage
  • Iceberg
  • Oracle
  • Redshift
  • S3
  • Snowflake
  • Spark
  • Trino
  • Airflow
  • SQL Server
Source — Tool mentions in context
- Data modeling – Kimbal, Denormalization, Dimensional, medallion schema patterns, bridge tables, marts, PK, FK, Clustering, and Tuning Implications - Languages – SQL, Python, Java, Javascript, Scala, Spark, Notebooks, Snowpark - LINUX – Must Know Linux, comfortable with EC2 servers, VI, cat, more etc.
3. Data Virtualization & Federated Access - Architect data virtualization patterns to enable logical access to data across Snowflake, Databricks, Oracle, SQL Server, and legacy NAS/file systems without physical movement - Define use cases for:- Federated queries (Snowflake external tables, Databricks Lakehouse Federation, Trino/Starburst, Denodo)
- Window/SLA‑driven batch processing with monitoring and rerun safety - Migration of legacy stored procedures, PL/SQL, and shell‑based ETL to cloud‑native equivalents - Hybrid batch + streaming patterns (medallion, change data capture)
- Establish batch performance, cost, and resiliency standards, including Reprocessing, Transaction Rollback, Event Logging, Query Timeout Limits, Warehouse Credit Limits, Finding/Flagging Expensive Processes from Account Usage Tables. - Partner with application owners to retire legacy infrastructure as part of data center exit and cloud migration programs. Previous Redshift, DB2, SQL Server experience is a help for migrating off of these platforms and data conversion issues that arise. - Identify Out of Date Drivers and Application Versions that could be Security Risks, and Advise Applications Teams what to upgrade to, so teams modernize while migrating.
- Data virtualization – Denodo, Starburst, Snowflake/Databricks federation, logical data fabric - Batch modernization – Migration from Oracle/PL‑SQL, mainframe, Unix ETL, Control‑M to cloud‑native orchestration - Multi‑cloud – AWS, Azure, GCP (storage, IAM, networking, private link)
- Contribute Designs, Patterns, Assets to SSIM Center of Excellence which establishes Best Practices for each platform as well as use cases for Reuse. - Lead Iceberg/Horizon/Unity Catalog interoperability across AWS, Azure, and GCP 2. Open Platforms & Open Table Formats
- Align with GCS data residency, isolation, and classification standards 6. Multi‑Cloud Platform Engineering (AWS / Azure / GCP) - Architect cloud‑native integrations across S3, ADLS, GCS, IAM, networking, and private link patterns
- Batch modernization – Migration from Oracle/PL‑SQL, mainframe, Unix ETL, Control‑M to cloud‑native orchestration - Multi‑cloud – AWS, Azure, GCP (storage, IAM, networking, private link) - Data modeling – Kimbal, Denormalization, Dimensional, medallion schema patterns, bridge tables, marts, PK, FK, Clustering, and Tuning Implications
Role Purpose The Senior Data Platform Architect is responsible for the end‑to‑end architecture, security design, and governance of SSIM's enterprise data platform spanning Snowflake, Databricks, open data platforms (Iceberg/Parquet/Delta), and data virtualization. Requires previous experience supporting workloads in analytics, regulatory reporting, AI/ML, and batch applications. The person in this role will ensure the modern platform meets financial‑services regulatory expectations, enterprise security standards (GCS/IAM), and data protection requirements (NPPI/PII). They Will Enable scalable, interoperable delivery across Investment Management use cases.
1. Data Platform Architecture & Integration - Define and govern the hybrid Snowflake–Databricks architecture to support classic Data Warehousing as well as Data Lake designs, aligning Snowflake's governed analytics layer with Databricks' engineering, streaming, and ML capabilities - Establish reference blueprints, patterns using lakehouse and medallion patterns suited for enterprise scale and auditability.
- Schema evolution, partitioning, and time‑travel - Cross‑engine compatibility (Snowflake, Databricks, Trino, Spark, Athena) - Catalog federation across Horizon, Unity, Glue, and Polaris
- Architect data virtualization patterns to enable logical access to data across Snowflake, Databricks, Oracle, SQL Server, and legacy NAS/file systems without physical movement - Define use cases for:- Federated queries (Snowflake external tables, Databricks Lakehouse Federation, Trino/Starburst, Denodo) - Virtual data products for analytics and reporting
4. Batch Application Solutioning & Modernization - Lead architecture and solutioning for batch applications migrating from legacy platforms (Oracle, mainframe, Unix/Linux ETL, file‑based workflows) to Snowflake/Databricks - Define patterns for:- Batch ingestion and orchestration (Airflow, Databricks Workflows, Snowflake Tasks/Streams, Control‑M integration)
- Lead architecture and solutioning for batch applications migrating from legacy platforms (Oracle, mainframe, Unix/Linux ETL, file‑based workflows) to Snowflake/Databricks - Define patterns for:- Batch ingestion and orchestration (Airflow, Databricks Workflows, Snowflake Tasks/Streams, Control‑M integration) - Window/SLA‑driven batch processing with monitoring and rerun safety
- Knowledge of Network Address White Listing. - Knowledge of Cloud Level Roles and Security Integrations and how they enable data access with Snowflake Horizon and Databricks Unity Catalog additional features. - Ensure compliance with SOX, MRAs, internal/external audits, and data protection controls
7. Delivery, SME Leadership & Stakeholder Engagement - Act as SME for Snowflake, Databricks, open platforms, virtualization, and batch modernization during architecture reviews and escalations - Partner with Security (GCS/GTS), Risk, Audit, Application, and Cloud Engineering teams
- Snowflake – WH Sizing, Object Hierarchy, Snowsight, RBAC, Horizon Catalog, governance, performance, data sharing, External Tables, Stages, Loading, SPs, Scripts, Snowpark - Databricks – Spark, Unity Catalog, ML pipelines, Delta/Iceberg, Lakehouse Federation - Open platforms – Apache Iceberg, Delta Lake, Parquet, Polaris, Trino/Starburst
- Open platforms – Apache Iceberg, Delta Lake, Parquet, Polaris, Trino/Starburst - Data virtualization – Denodo, Starburst, Snowflake/Databricks federation, logical data fabric - Batch modernization – Migration from Oracle/PL‑SQL, mainframe, Unix ETL, Control‑M to cloud‑native orchestration
2. Open Platforms & Open Table Formats - Architect open data platform strategy leveraging Apache Iceberg, Delta Lake, Parquet, and Polaris/Unity Catalog to avoid vendor lock‑in and enable cross‑engine query - Define standards for open table format adoption, including:- Business Tool Access Protocols, Drivers, Standards
- Databricks – Spark, Unity Catalog, ML pipelines, Delta/Iceberg, Lakehouse Federation - Open platforms – Apache Iceberg, Delta Lake, Parquet, Polaris, Trino/Starburst - Data virtualization – Denodo, Starburst, Snowflake/Databricks federation, logical data fabric
The Senior Data Platform Architect is responsible for the end‑to‑end architecture, security design, and governance of SSIM's enterprise data platform spanning Snowflake, Databricks, open data platforms (Iceberg/Parquet/Delta), and data virtualization. Requires previous experience supporting workloads in analytics, regulatory reporting, AI/ML, and batch applications. The person in this role will ensure the modern platform meets financial‑services regulatory expectations, enterprise security standards (GCS/IAM), and data protection requirements (NPPI/PII). They Will Enable scalable, interoperable delivery across Investment Management use cases. This role is hands‑on, decision‑critical, and risk‑bearing, with accountability for architectural choices that directly impact regulatory compliance, audit defensibility, and business continuity. Platform Designs must be Secure, Scalable, include Disaster Recovery, as well as Data Sharing capabilities. Design and Build monitoring as well as chargeback models for billing back to application teams.
- Maintain defensible audit trails, lineage, and forensic traceability - Align with GCS data residency, isolation, and classification standards 6. Multi‑Cloud Platform Engineering (AWS / Azure / GCP)
6. Multi‑Cloud Platform Engineering (AWS / Azure / GCP) - Architect cloud‑native integrations across S3, ADLS, GCS, IAM, networking, and private link patterns - Drive cross‑region/cross‑cloud HA/DR designs including Snowgrid replication and Iceberg federation
- Act as SME for Snowflake, Databricks, open platforms, virtualization, and batch modernization during architecture reviews and escalations - Partner with Security (GCS/GTS), Risk, Audit, Application, and Cloud Engineering teams - Produce architecture diagrams, design artifacts, executive‑level presentations, and access models
Required Skills & Experience - Snowflake – WH Sizing, Object Hierarchy, Snowsight, RBAC, Horizon Catalog, governance, performance, data sharing, External Tables, Stages, Loading, SPs, Scripts, Snowpark - Databricks – Spark, Unity Catalog, ML pipelines, Delta/Iceberg, Lakehouse Federation

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability.

In the employer’s words · Read in context

Job description

View original posting ↗

Role Purpose

The Senior Data Platform Architect is responsible for the end‑to‑end architecture, security design, and governance of SSIM's enterprise data platform spanning Snowflake, Databricks, open data platforms (Iceberg/Parquet/Delta), and data virtualization.  Requires previous experience supporting workloads in analytics, regulatory reporting, AI/ML, and batch applications.

The person in this role will ensure the modern platform meets financial‑services regulatory expectations, enterprise security standards (GCS/IAM), and data protection requirements (NPPI/PII).    They Will Enable scalable, interoperable delivery across Investment Management use cases.

This role is hands‑on, decision‑critical, and risk‑bearing, with accountability for architectural choices that directly impact regulatory compliance, audit defensibility, and business continuity.  Platform Designs must be Secure, Scalable, include Disaster Recovery, as well as Data Sharing capabilities.  Design and Build monitoring as well as chargeback models for billing back to application teams.

Core Responsibilities

1. Data Platform Architecture & Integration

  • Define and govern the hybrid Snowflake–Databricks architecture to support classic Data Warehousing as well as Data Lake designs, aligning Snowflake's governed analytics layer with Databricks' engineering, streaming, and ML capabilities
  • Establish reference blueprints, patterns using lakehouse and medallion patterns suited for enterprise scale and auditability. 
  • Contribute Designs, Patterns, Assets to SSIM Center of Excellence which establishes Best Practices for each platform as well as use cases for Reuse.
  • Lead Iceberg/Horizon/Unity Catalog interoperability across AWS, Azure, and GCP

2. Open Platforms & Open Table Formats

  • Architect open data platform strategy leveraging Apache Iceberg, Delta Lake, Parquet, and Polaris/Unity Catalog to avoid vendor lock‑in and enable cross‑engine query
  • Define standards for open table format adoption, including:
    • Business Tool Access Protocols, Drivers, Standards
    • Naming Standards, Folder Structures, Cloud Storage Security
    • Schema evolution, partitioning, and time‑travel
    • Cross‑engine compatibility (Snowflake, Databricks, Trino, Spark, Athena)
    • Catalog federation across Horizon, Unity, Glue, and Polaris
  • Establish governance for open formats in regulated workloads (lineage, access control, encryption)
  • Drive interoperability between proprietary and open ecosystems to support modernization and exit strategies
  • Capture Feedback, Fialings, Suggestions form the Users an Provide that Distilled information back to Vendors to Improve their Offerings

3. Data Virtualization & Federated Access

  • Architect data virtualization patterns to enable logical access to data across Snowflake, Databricks, Oracle, SQL Server, and legacy NAS/file systems without physical movement
  • Define use cases for:
    • Federated queries (Snowflake external tables, Databricks Lakehouse Federation, Trino/Starburst, Denodo)
    • Virtual data products for analytics and reporting
    • Logical data fabric spanning cloud and on‑prem sources
  • Establish guardrails for performance, cost, security, and data classification in virtualized access patterns
  • Reduce data duplication, copy proliferation, and storage cost through virtualization where appropriate

4. Batch Application Solutioning & Modernization

  • Lead architecture and solutioning for batch applications migrating from legacy platforms (Oracle, mainframe, Unix/Linux ETL, file‑based workflows) to Snowflake/Databricks
  • Define patterns for:
    • Batch ingestion and orchestration (Airflow, Databricks Workflows, Snowflake Tasks/Streams, Control‑M integration)
    • Window/SLA‑driven batch processing with monitoring and rerun safety
    • Migration of legacy stored procedures, PL/SQL, and shell‑based ETL to cloud‑native equivalents
    • Hybrid batch + streaming patterns (medallion, change data capture)
  • Establish batch performance, cost, and resiliency standards, including Reprocessing, Transaction Rollback, Event Logging, Query Timeout Limits, Warehouse Credit Limits, Finding/Flagging Expensive Processes from Account Usage Tables.
  • Partner with application owners to retire legacy infrastructure as part of data center exit and cloud migration programs.  Previous Redshift, DB2, SQL Server experience is a help for migrating off of these platforms and data conversion issues that arise.
  • Identify Out of Date Drivers and Application Versions that could be Security Risks, and Advise Applications Teams what to upgrade to, so teams modernize while migrating.

5. Security, Governance & Regulatory Alignment

  • Architect and enforce data security by design, including:
    • Design RBAC Roles at a Group Level for R, RW, Admin at the DB, Schema, Object Levels.  This should balance security needs with what is reasonable overhead to Administrate.
    • Advise on Lower Level Row Access Policy, Column Masking, Secure Views so App Teams have row‑level and column‑level security where necessary.
    • Familiar with Establishing Future Grants
    • Knowledge of Managed Access Schemas and trade offs.
    • Knowledge of Network Address White Listing. 
    • Knowledge of Cloud Level Roles and Security Integrations and how they enable data access with Snowflake Horizon and Databricks Unity Catalog additional features.
  • Ensure compliance with SOX, MRAs, internal/external audits, and data protection controls
  • Maintain defensible audit trails, lineage, and forensic traceability
  • Align with GCS data residency, isolation, and classification standards

6. Multi‑Cloud Platform Engineering (AWS / Azure / GCP)

  • Architect cloud‑native integrations across S3, ADLS, GCS, IAM, networking, and private link patterns
  • Drive cross‑region/cross‑cloud HA/DR designs including Snowgrid replication and Iceberg federation
  • Ensure vendor security, networking real‑time/streaming, and disaster recovery are embedded in design

7. Delivery, SME Leadership & Stakeholder Engagement

  • Act as SME for Snowflake, Databricks, open platforms, virtualization, and batch modernization during architecture reviews and escalations
  • Partner with Security (GCS/GTS), Risk, Audit, Application, and Cloud Engineering teams
  • Produce architecture diagrams, design artifacts, executive‑level presentations, and access models

Required Skills & Experience

  • Snowflake – WH Sizing, Object Hierarchy, Snowsight, RBAC, Horizon Catalog, governance, performance, data sharing, External Tables, Stages, Loading, SPs, Scripts, Snowpark
  • Databricks – Spark, Unity Catalog, ML pipelines, Delta/Iceberg, Lakehouse Federation
  • Open platforms – Apache Iceberg, Delta Lake, Parquet, Polaris, Trino/Starburst
  • Data virtualization – Denodo, Starburst, Snowflake/Databricks federation, logical data fabric
  • Batch modernization – Migration from Oracle/PL‑SQL, mainframe, Unix ETL, Control‑M to cloud‑native orchestration
  • Multi‑cloud – AWS, Azure, GCP (storage, IAM, networking, private link)
  • Data modeling – Kimbal, Denormalization, Dimensional, medallion schema patterns, bridge tables, marts, PK, FK, Clustering, and Tuning Implications
  • Languages – SQL, Python, Java, Javascript, Scala, Spark, Notebooks, Snowpark
  • LINUX – Must Know Linux, comfortable with EC2 servers, VI, cat, more etc.
  • Regulated industry experience – Financial Services, SOX, MRA, audit, NPPI/PII handling
  • Generative AI – Comfortable with Scripting and prompting.  Understand when scripting is going to be more efficient and able to generate good scripts using well defined prompts and skill files.
  • Good Team and Communication Skills – Being Comfortable and willing to share your knowledge as well as learn from others.  Coordinates well with other team members, project managers, and other teams.  The World is Accelerating and we are all learning together to navigate the new changes to build Best in Class Platforms.

Salary Range:

$120,000 - $202,500 Annual

The 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

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Pay
Salary Range: $120,000 - $202,500 Annual The 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.
Location & working pattern

Boston, Massachusetts

1. Data Platform Architecture & Integration - Define and govern the hybrid Snowflake–Databricks architecture to support classic Data Warehousing as well as Data Lake designs, aligning Snowflake's governed analytics layer with Databricks' engineering, streaming, and ML capabilities - Establish reference blueprints, patterns using lakehouse and medallion patterns suited for enterprise scale and auditability.
More source context
- Migration of legacy stored procedures, PL/SQL, and shell‑based ETL to cloud‑native equivalents - Hybrid batch + streaming patterns (medallion, change data capture) - Establish batch performance, cost, and resiliency standards, including Reprocessing, Transaction Rollback, Event Logging, Query Timeout Limits, Warehouse Credit Limits, Finding/Flagging Expensive Processes from Account Usage Tables.

More relevant text appears in the full description.

Work authorization
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
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