Senior Manager / Senior Software Engineer – Distribution Analytics, Data Products & AI

Ameriprise Financial Services, LLC•Boston, MA

2d•$131,700 - $181,000•Hybrid

About The Position

We are seeking a highly skilled Senior Manager / Senior Data Engineer to lead the design, development, and delivery of data products, analytics solutions, business intelligence capabilities, and AI-powered applications supporting the Asset Management Distribution organization. This role is a senior technical leadership position focused on transforming data into actionable insights, scalable data products, and intelligent business solutions. The successful candidate will partner closely with Distribution, Sales, Marketing, National Accounts, Client Service, and Technology teams to deliver analytics and AI capabilities that drive growth, improve productivity, and enhance decision-making. The ideal candidate brings deep expertise in data engineering, business intelligence, analytics, and Generative AI, combined with a strong understanding of asset management distribution, client, sales and marketing data. This role emphasizes hands-on solution delivery, technical leadership, and business partnership responsibilities. Success in this role: Deliver trusted data products, impactful analytics, and AI-powered capabilities that enhance business decision-making, improve productivity, and drive measurable outcomes across the Distribution organization.

Requirements

Bachelors degree in Computer Science, Engineering, related field, or equivalent relevant work experience.
7-10 years of relevant experienced required.
Deep and broad technical background with 7-10+ years experience of Data Engineering, Analytics Engineering, Business Intelligence, or related disciplines.
3-5+ years of project management experience with a proven track record for delivering projects and driving execution.
Demonstrated experience and success in influencing, leading, and coaching without direct leadership responsibility.
Advanced expertise in Python, SQL, data modeling, ETL/ELT development, and cloud-based data warehousing platforms such as Snowflake or Amazon Redshift.
Experience with BI and analytics tools such as Tableau, Power BI or similar platforms.
Hands-on experience building AI-enabled applications using technologies such as Anthropic Claude, OpenAI, Amazon Bedrock, Azure OpenAI,Strands, AgentCore, or similar frameworks.
Experience developing RAG solutions and integrating enterprise data into AI-powered workflows and applications.
Strong understanding of data warehousing, dimensional modeling, semantic models, data governance, metadata management, and data quality practices.
Demonstrated ability to lead cross-functional initiatives, influence stakeholders, and provide technical leadership and mentorship.

Nice To Haves

Experience in Asset Management, Wealth Management, Investment Management, or Financial Services.
Strong understanding of asset management distribution, sales, marketing, client, account, investment, and performance data domains.
Experience building analytics, AI, or data products for Distribution, Sales, Marketing, Client Service, or Executive leadership teams.
Familiarity with Salesforce CRM, or similar industry platforms.
Experience with Snowflake Cortex, semantic models, conversational analytics, AI copilots, or agentic AI solutions.
AWS Data Engineering, Analytics, AI/ML, or Solution Architect certifications.
Experience with MLOps, AI governance, and responsible AI frameworks.

Responsibilities

Design, develop, and deliver business-critical data products, analytics solutions, dashboards, and AI-powered applications.
Partner with business stakeholders to define requirements, prioritize opportunities, and deliver data-driven solutions that address strategic business needs.
Build and optimize scalable data pipelines, semantic models, and analytical data assets that support reporting, advanced analytics, and AI use cases.
Lead the development of business intelligence solutions and executive reporting capabilities that provide insights into sales performance, client engagement, marketing effectiveness, AUM growth, and business outcomes.
Design and implement Generative AI and Retrieval-Augmented Generation (RAG) solutions leveraging enterprise data and modern AI technologies.
Develop reusable services, APIs, and frameworks that accelerate analytics and AI adoption across the organization.
Ensure data quality, governance, metadata management, and consistency of business metrics across solutions.
Provide technical leadership, architecture guidance, and mentorship to engineering and analytics teams.
Evaluate emerging technologies and identify opportunities to enhance business capabilities through analytics, automation, and AI innovation.
Collaborate with cross-functional teams to drive successful delivery of high-impact data and AI initiatives.