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

Senior Data Platform ArchitectThe 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 ResponsibilitiesData Platform Architecture & IntegrationDefine 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 capabilitiesEstablish 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 GCPOpen Platforms & Open Table FormatsArchitect open data platform strategy leveraging Apache Iceberg, Delta Lake, Parquet, and Polaris/Unity Catalog to avoid vendor lock-in and enable cross-engine queryDefine standards for open table format adoption, including:Business Tool Access Protocols, Drivers, StandardsNaming Standards, Folder Structures, Cloud Storage SecuritySchema evolution, partitioning, and time-travelCross-engine compatibility (Snowflake, Databricks, Trino, Spark, Athena)Catalog federation across Horizon, Unity, Glue, and PolarisEstablish governance for open formats in regulated workloads (lineage, access control, encryption)Drive interoperability between proprietary and open ecosystems to support modernization and exit strategiesCapture Feedback, Failures, Suggestions form the Users and Provide that Distilled information back to Vendors to Improve their OfferingsData Virtualization & Federated AccessArchitect data virtualization patterns to enable logical access to data across Snowflake, Databricks, Oracle, SQL Server, and legacy NAS/file systems without physical movementDefine use cases for:Federated queries (Snowflake external tables, Databricks Lakehouse Federation, Trino/Starburst, Denodo)Virtual data products for analytics and reportingLogical data fabric spanning cloud and on-prem sourcesEstablish guardrails for performance, cost, security, and data classification in virtualized access patternsReduce data duplication, copy proliferation, and storage cost through virtualization where appropriateBatch Application Solutioning & ModernizationLead architecture and solutioning for batch applications migrating from legacy platforms (Oracle, mainframe, Unix/Linux ETL, file-based workflows) to Snowflake/DatabricksDefine patterns for:Batch ingestion and orchestration (Airflow, Databricks Workflows, Snowflake Tasks/Streams, Control-M integration)Window/SLA-driven batch processing with monitoring and rerun safetyMigration of legacy stored procedures, PL/SQL, and shell-based ETL to cloud-native equivalentsHybrid 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.Security, Governance & Regulatory AlignmentArchitect 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 GrantsKnowledge 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 controlsMaintain defensible audit trails, lineage, and forensic traceabilityAlign with GCS data residency, isolation, and classification standardsMulti-Cloud Platform Engineering (AWS / Azure / GCP)Architect cloud-native integrations across S3, ADLS, GCS, IAM, networking, and private link patternsDrive cross-region/cross-cloud HA/DR designs including Snowgrid replication and Iceberg federationEnsure vendor security, networking real-time/streaming, and disaster recovery are embedded in designDelivery, SME Leadership & Stakeholder EngagementAct as SME for Snowflake, Databricks, open platforms, virtualization, and batch modernization during architecture reviews and escalationsPartner with Security (GCS/GTS), Risk, Audit, Application, and Cloud Engineering teamsProduce architecture diagrams, design artifacts, executive-level presentations, and access modelsRequired Skills & ExperienceSnowflake – WH Sizing, Object Hierarchy, Snowsight, RBAC, Horizon Catalog, governance, performance, data sharing, External Tables, Stages, Loading, SPs, Scripts, SnowparkDatabricks – Spark, Unity Catalog, ML pipelines, Delta/Iceberg, Lakehouse FederationOpen platforms – Apache Iceberg, Delta Lake, Parquet, Polaris, Trino/StarburstData virtualization – Denodo, Starburst, Snowflake/Databricks federation, logical data fabricBatch modernization – Migration from Oracle/PL-SQL, mainframe, Unix ETL, Control-M to cloud-native orchestrationMulti-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 ImplicationsLanguages – SQL, Python, Java, Javascript, Scala, Spark, Notebooks, SnowparkLINUX – Must Know Linux, comfortable with EC2 servers, VI, cat, more etc.Regulated industry experience – Financial Services, SOX, MRA, audit, NPPI/PII handlingGenerative 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