Principal Enterprise Data & Analytics Architect

Russell Investments is seeking a Principal Enterprise Data & Analytics Architect to lead the design, implementation, and modernization of the firm's enterprise data and analytics architecture in a hybrid environment. This role involves defining the data architecture roadmap, developing design patterns, optimizing data warehouse solutions, leading data modeling efforts, and implementing MDM strategies. The architect will also drive cloud migration initiatives, integrate legacy systems, and enable AI/ML-ready data environments, partnering with various business units to deliver scalable data products.

Must Have

• Define and maintain the enterprise data architecture roadmap.
• Develop reference architectures, design patterns, and reusable components for data.
• Partner with domain engineering and analytics teams to design interoperable data solutions.
• Lead architectural review sessions and ensure governance alignment.
• Architect and optimize data warehouse and data lakehouse solutions.
• Lead enterprise-wide data modeling efforts.
• Champion the use of canonical models and metadata standards.
• Design robust data warehouse architectures.
• Define and implement the enterprise MDM strategy.
• Integrate data quality, metadata, and lineage frameworks.
• Lead cloud migration initiatives for legacy data platforms.
• Define migration patterns, cut-over strategies, and hybrid data access architectures.
• Maintain deep familiarity with legacy database technologies, particularly Microsoft SQL Server.
• Architect AI/ML-ready data environments.
• Partner with technology and analytics teams across business domains.
• 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 where real-time data is required.
• Support adoption of federated data architecture principles.

Good to Have

• 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.
• Hands-on exposure or background in machine learning, AI model lifecycle management, or MLOps frameworks (e.g., SageMaker, Azure ML, MLflow).

Perks & Benefits

• Annual performance bonus
• Healthcare benefits
• Retirement benefits
• Vacation
• Wellbeing programs

Business Unit:

Global Technology

Salary Range:

$160,000 USD - $190,000 USD

Specific compensation will be based on candidate’s experience, skills, qualifications, commercial considerations, and other job-related factors permitted by law. At Russell Investments, salary is just one part of our compensation package. Our total rewards approach includes an annual performance bonus (subject to eligibility criteria) in addition to participation in our competitive benefits programs including healthcare, retirement, vacation, and wellbeing programs.

Job Description:

Russell Investments is seeking a Principal Enterprise Data & Analytics Architect to join our Enterprise Data Office (EDO) within the Technology organization. The EDO functions as a horizontal capability, enabling enterprise data architecture, governance, engineering, and analytics enablement across all lines of business. This role will lead the design, implementation, and modernization of Russell’s enterprise data and analytics architecture in a hybrid environment (on-premises + cloud). The Architect will bridge enterprise technology teams (DevOps, Production Support, Cloud Platform) and domain-aligned teams across multiple business verticals — driving excellence in data modeling, master data management, data warehouse design, and AI/ML-ready architecture patterns.

Key Responsibilities

Enterprise & Solution Architecture

• Define and maintain the enterprise data architecture roadmap aligned with the firm’s technology strategy and business objectives.
• Develop reference architectures, design patterns, and reusable components for data ingestion, transformation, modeling, and analytics.
• Partner with domain engineering and analytics teams to design fit-for-purpose, interoperable data solutions that align with enterprise standards.
• Lead architectural review sessions and ensure governance alignment across all domains.
• Serve as an advisor to leadership on data strategy, modernization, and investment prioritization.

Data Platform, Modeling & Warehouse Design

• 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.

Master Data Management (MDM) & Data Governance

• 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.

Cloud Modernization & Migration

• 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.

Legacy Systems Integration

• 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.

Emerging Technologies & AI/ML Enablement

• 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.
• Nice to have: Hands-on exposure or background in machine learning, AI model lifecycle management, or MLOps frameworks (e.g., SageMaker, Azure ML, MLflow).

Cross-Domain Solution Delivery

• 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.

Platform Modernization & Transformation

• 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.

Qualifications

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.

Soft Skills & Leadership

Strategic thinker with ability to translate architecture into business outcomes. Strong influencer who can align stakeholders across federated data domains. Collaborative, pragmatic, and capable of mentoring other architects and engineers. Comfortable operating across multiple business units and global teams.

Education

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field. Advanced technical certifications preferred.

Success Metrics

• Adoption of standardized enterprise data models and MDM frameworks.
• Successful cloud migration of key legacy systems.
• Improved time-to-insight and AI/ML readiness of data platforms.
• Reduction in data redundancy and improved quality across domains.
• Measurable improvement in governance, lineage, and cost efficiency.

Compensation & Level

Job Level: Principal / Senior Architect Compensation Band: • Base salary: TBD (commensurate with experience & location) • Target bonus: TBD • Work model: 4 days on-site, 1 day remote

This role is not eligible for employment-based immigration sponsorship. Applicants must be legally authorized to work in the United States without employer sponsorship, now or in the future.

Equal Employment Opportunity

Russell Investments is committed to providing equal employment opportunities for all associates and employment applicants regardless of race, religion, ancestry, creed, color, gender (including gender identity which refers to a person's actual or perceived sex, and includes self-image, appearance, behavior or expression, whether or not different from that traditionally associated with a person's biological sex), age, national origin, citizenship status, disability, medical condition, military status, veteran status, marital status, sexual orientation, past or present unemployment status , or any other characteristic protected by law.