Russell Investments ยท 1 month ago
Principal Enterprise Data & Analytics Architect
New York
Full-time
Hybrid
Lead/Staff
$160K/yr - $190K/yr
10+ years expRussell Investments is seeking a Principal Enterprise Data & Analytics Architect to join their Enterprise Data Office within the Technology organization. This role will lead the design, implementation, and modernization of enterprise data and analytics architecture, ensuring excellence in data modeling, master data management, and cloud migration initiatives.
Financial Services
No H1B
Responsibilities
Architect and optimize data warehouse and data lakehouse solutions leveraging modern cloud data platforms (Snowflake, Databricks, Azure/AWS) integrated with on-prem databases
Lead enterprise-wide data modeling efforts (conceptual, logical, and physical) to ensure consistency, performance, and scalability across domains
Champion the use of canonical models and metadata standards to support semantic alignment and data product reuse
Design robust data warehouse architectures that support analytical, regulatory, and operational workloads, with a strong foundation in dimensional modeling and data vault methodologies
Collaborate with BI and Analytics teams to define semantic and business layers that enable self-service analytics
Define and implement the enterprise MDM strategy ensuring consistency and accuracy of critical master and reference data (Client, Product, Account, Instrument, Legal Entity)
Integrate data quality, metadata, and lineage frameworks within all architectural designs
Partner with governance and stewardship teams to enforce data ownership, classification, and privacy controls
Promote the 'data as a product' mindset across business domains
Lead cloud migration initiatives for legacy data platforms (SQL Server, Oracle, and other on-prem systems) to modern cloud environments
Define migration patterns, cut-over strategies, and hybrid data access architectures
Partner with infrastructure and DevOps teams to implement CI/CD pipelines, Infrastructure-as-Code, and automated provisioning for data platforms
Ensure designs address scalability, security, cost optimization, and resiliency
Maintain deep familiarity with legacy database technologies, particularly Microsoft SQL Server, and design hybrid patterns that enable interoperability with modern cloud solutions
Provide guidance on data extraction, replication, and real-time synchronization between legacy and cloud systems
Serve as a subject-matter expert in SQL Server architecture, performance tuning, and optimization as part of the broader modernization roadmap
Architect AI/ML-ready data environments by ensuring pipelines and models support feature engineering, versioning, and reproducibility
Collaborate with data scientists and ML engineers to define data provisioning, model training, and inferencing pipelines integrated into enterprise data architecture
Define data lineage, observability, and quality frameworks that ensure trust in AI/ML outputs
Partner with technology and analytics teams across Investments, GTM/Sales (Retail & Institutional), Marketing, Finance, HR, Risk & Performance, and Legal to deliver scalable data products
Translate business requirements into logical and physical data models, reusable domain data pipelines, and shared data assets
Drive architectural consistency and interoperability across verticals
Lead modernization initiatives to transition from legacy on-prem systems to cloud and hybrid architectures
Introduce event-driven and streaming patterns (Kafka, Event Hubs) where real-time data is required
Support adoption of federated data architecture principles (Data Mesh) within defined enterprise guardrails
Qualification
Required
10+ years of experience in data architecture, data engineering, or enterprise data solution design
10+ years of experience in SQL and advanced concepts
3+ years with DBT and familiarity with advanced concepts
5+ years designing cloud-based data platforms (Azure preferred)
Proven expertise in data modeling and data warehouse design (3NF, dimensional, Data Vault)
Hands-on experience with Master Data Management (MDM) strategy and implementation
Demonstrated success leading cloud migration projects and designing hybrid architectures
Strong proficiency in SQL Server and relational database optimization
Knowledge of metadata management, data governance, data quality, and lineage
Excellent communication and stakeholder management across technical and business domains
Preferred
Experience in investment management, asset management, or financial services
Familiarity with AI/ML architectural patterns, feature stores, and model lifecycle integration
Exposure to Python, Spark, or Databricks for data transformation and ML pipelines
Experience with data observability tools (e.g., Monte Carlo, Great Expectations, Datafold)
Certifications in Snowflake, Databricks, or Cloud Data Architecture a plus
Benefits
Annual performance bonus (subject to eligibility criteria)
Participation in our competitive benefits programs including healthcare, retirement, vacation, and wellbeing programs
Company
Russell Investments
Russell Investment Group a global leader in multi-manager investment services, provides investment products
1001-5000 employees
Funding
Current Stage
Late StageTotal Funding
unknown2015-10-08Acquired
Leadership Team
Zach Buchwald
Chairman and Chief Executive Officer
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