Director, Analytics Technology

Fidelity will not provide immigration sponsorship for this position.

Job Description:

Director, Analytics Technology

The Role We are seeking a Director of Analytics Technology to join our Workplace Investing (WI) Experimentation & Measurement team. As a senior member on a multi-disciplinary technology team, you will help build and scale best-in-class measurement and analytics capabilities that enable data-driven decision making across the  this role, you will partner closely with Product, Marketing, Data Science, Analytics, and Technology leaders to design and deliver modern data and measurement solutions that support experimentation, personalization, AI/ML initiatives, and business growth.

You will play a critical role in transforming complex data into trusted, scalable assets that accelerate insights, improve decision quality, and drive measurable outcomes.

This position requires a unique combination of analytics, engineering expertise, and strategic thinking to help Fidelity continue advancing its experimentation and personalization capabilities.

Key Responsibilities Lead the design, development, and optimization of scalable data models, data products, and measurement solutions that support experimentation and personalization initiatives.

Translate business and measurement requirements into robust data architectures, data pipelines, and reusable analytics assets.

Partner with architects, technical leads, product managers, data scientists, and analytics teams to define and implement enterprise-grade data solutions.

Build and maintain modern ETL/ELT frameworks and scalable data transformation processes in cloud environments.

Develop trusted data assets, views, and semantic layers that enable self-service analytics and advanced measurement capabilities.

Establish and enforce data quality, governance, lineage, and documentation standards using tools such as Alation.

Drive performance optimization across databases, queries, pipelines, and data models to improve scalability and reliability.

Support the development of experimentation and measurement frameworks that enable faster learning and more effective business decisions.

Champion engineering best practices including CI/CD, Dev Ops, testing, observability, and automation.

Mentor and develop members of the team while fostering a culture of continuous improvement, innovation, and technical excellence.

Identify opportunities to leverage AI-powered engineering and developer productivity tools to accelerate delivery and improve solution quality.

Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
10+ years of experience in data engineering, analytics engineering, data warehousing, or related disciplines.

Advanced proficiency in SQL and experience with modern relational and cloud-based databases such as Snowflake and Oracle.

Strong experience designing and implementing scalable data models and analytics solutions.

Hands-on experience with Python and modern data processing frameworks.

Deep understanding of data warehousing, dimensional modeling, and analytical data architectures.

Experience developing cloud-native data solutions within AWS environments.

Experience building and maintaining ETL/ELT pipelines and orchestration frameworks.

Working Knowledge of business intelligence and visualization platforms such as Power BI and Tableau.

Experience with CI/CD and Dev Ops practices leveraging tools such as Git Hub, Jenkins, and automated deployment frameworks such as Control-M.Understanding of data governance, metadata management, data lineage, and data quality best practices.

Strong analytical, problem-solving, and solution design capabilities.

Proven ability to influence stakeholders and communicate complex technical concepts to both technical and non-technical audiences.

Demonstrated experience leading, mentoring, and developing technical talent.

Preferred Qualifications Experience supporting experimentation platforms, A/B testing, causal measurement, or test-and-learn programs.

Understanding of digital analytics, customer personalization, and measurement frameworks.

Familiarity with advanced analytics and data science concepts, including machine learning applications.

Experience leveraging GenAI-enabled development tools, including Git Hub Copilot, AI-assisted coding workflows, and agent-based engineering practices.

Financial services or highly regulated industry experience.

The Team You will be part of Fidelity's Workplace Investing…