{"id":2884922,"url":"https://alion.io/job/standard-product-manager-data-ai-platform","title":"Product Manager - Data & AI Platform","company":{"id":1808171,"name":"Standard","domain":"standard.com","url":"https://alion.io/company/standard-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"Product","role_family":"Product","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Portland, United States","United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":109750,"max":186500,"currency":"USD","period":"year","gross":null,"usd_annual":186500},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Embeddings","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-19T23:57:32Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-23T08:39:27Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"The next part of your journey is right around the corner - with The Standard.\nA genuine desire to make a difference in the lives of others is the foundation for everything we do. With a customer-first mindset and an intentional focus on building strong teams, we’ve been able to uphold our legacy of financial stability while investing in new, innovative technologies that support the needs of our customers. Our high-performance culture focused on operational excellence thrives thanks to remarkable people united by compassion and a customer-first commitment. Are you ready to make a difference?\nJob Summary\nAt The Standard, Agile Product Managers connect customer needs, technical realities, and enterprise priorities. They work across teams to make clear tradeoffs and ensure technology investments deliver practical, measurable value.\nFor the Data & AI Platform, the primary customers are the teams building enterprise data, analytics, and AI products. This role turns their engineering needs into a platform strategy that makes enterprise data easier to discover, access, process, govern, and use.\nThe Product Manager - Data & AI Platform owns the strategy, roadmap, adoption, and value realization of the enterprise data platform, with Azure Databricks as a core technology.\nThis role partners closely with Data Platform Engineering, Architecture, Data Governance, Security, Data Product teams, and AI Product teams to build a scalable, governed, self-service data foundation.\nThe Product Manager develops a strong understanding of Databricks and modern data platform capabilities and uses that knowledge to prioritize platform investments, define reusable capabilities, establish self-service consumption patterns, and reduce friction for teams building Data and AI products.\nSuccess in this role means Data and AI teams can spend more time delivering business capabilities and less time building or navigating underlying data infrastructure.\nKey Responsibilities:\nData Platform Strategy & Roadmap\nOwn the product strategy and roadmap for the enterprise Data & AI Platform, with a strong focus on Databricks-based platform capabilities.\nTranslate the needs of Data Product and AI Product teams into platform capabilities, investment priorities, and measurable outcomes.\nPrioritize platform capabilities based on aggregate enterprise demand, reuse potential, consumer value, risk, and strategic alignment.\nPartner with Engineering and Architecture on the evolution of the Databricks lakehouse and its surrounding ecosystem.\nBalance new platform capabilities, modernization, technical debt, reliability, governance, and developer experience.\nMaintain a clear distinction between capabilities owned by the platform and capabilities owned by consuming product teams.\nDatabricks & Data Platform Capabilities\nDevelop strong working knowledge of Azure Databricks, Delta Lake, Unity Catalog, Databricks Workflows, Lakehouse architecture, Azure Data Lake, SQL, Python/PySpark, APIs, streaming, and related data-platform technologies.\nUnderstand common data engineering patterns including ingestion, transformation, orchestration, storage, governance, data quality, lineage, and serving.\nPartner with Engineering to define reusable platform capabilities and standardized patterns for batch, streaming, and other enterprise data workloads.\nDrive platform capabilities supporting governed data discovery, access, sharing, observability, quality, and lineage.\nHelp establish scalable patterns that allow data products to move from source ingestion through curated, reusable enterprise data.\nEnable Data & AI Product Teams\nTreat Data Product and AI Product teams as primary platform customers and deeply understand their workflows, technical dependencies, pain points, and emerging needs.\nEstablish platform consumption models that allow teams to build products without creating bespoke infrastructure.\nChampion self-service golden paths, reusable patterns, reference implementations, and standardized platform services.\nDrive capabilities that enable product teams to discover and consume trusted enterprise data.\nPartner with AI Product teams to understand data requirements for machine learning, GenAI, RAG, agentic, and other emerging AI workloads.\nPrioritize foundational capabilities that can be reused across multiple teams rather than solving repeatedly for individual projects.\nUse consumer feedback and adoption data to continuously improve the platform developer experience.\nData Governance & Enterprise Enablement\nPartner with Data Governance, Security, Privacy, Risk, and Architecture to ensure governance requirements are incorporated into platform capabilities.\nUnderstand and help prioritize Unity Catalog capabilities supporting access control, metadata, discovery, and lineage.\nPromote standardized approaches for managing sensitive and regulated enterprise data.\nBalance governance and risk requirements with the need for an efficient developer and data-consumer experience.\nDrive adoption of reusable, governed enterprise data rather than duplicated pipelines and siloed implementations.\nPlatform Adoption & Developer Experience\nOwn platform intake, onboarding, adoption, and consumer feedback processes.\nChampion simple, documented, self-service paths for common Data and AI development scenarios.\nIdentify recurring friction experienced by engineering teams and translate those problems into roadmap opportunities.\nPartner with Engineering to define appropriate service levels, support models, documentation, and consumption experiences.\nTrack platform adoption, reuse, onboarding experience, consumer satisfaction, reliability, and value realization.\nUse platform telemetry and consumer feedback to inform product decisions and investment priorities.\nCross-Functional Product Leadership\nPartner closely with Data Platform Engineering, Data Engineering, Architecture, Data Governance, Security, Analytics, Data Product Management, and AI Product Management.\nTranslate complex technical topics into clear product decisions, priorities, tradeoffs, and business outcomes.\nFacilitate decisions where multiple consuming teams have competing needs.\nCommunicate the platform roadmap and strategy to technical and business stakeholders.\nMaintain alignment between platform investment and enterprise Data & AI strategy.\nSkills and Background You’ll Need\nEducation: A High School Diploma or GED is required. A Bachelor’s degree is preferred.\nExperience: 5-7 years of progressive experience in a business or technology environment.\nExperience managing data platforms, cloud platforms, developer platforms, internal technology products, or technically complex enterprise products is strongly preferred.\nProduct Management Skills\nStrong product management, product strategy, roadmap development, prioritization, and stakeholder-management capabilities.\nDemonstrated ability to translate technical consumer needs into platform capabilities and investment priorities.\nExperience managing products supporting internal engineering or technical consumers.\nExperience using adoption, utilization, consumer feedback, and business outcomes to guide product decisions.\nAbility to balance near-term delivery needs with long-term platform strategy.\nData Platform Skills\nStrong understanding of modern cloud data platforms and lakehouse architecture.\nWorking knowledge of Azure Databricks and its role in enterprise data architectures.\nFamiliarity with Databricks capabilities such as Unity Catalog, Delta Lake, Workflows, notebooks, SQL and PySpark.\nUnderstanding of data ingestion, transformation, orchestration, storage, serving, and data-product patterns.\nUnderstanding of data governance concepts including metadata, lineage, data quality, access control, privacy, and security.\nFamiliarity with CI/CD, Git, APIs, event streaming, and cloud engineering practices.\nAbility to discuss data architecture and engineering tradeoffs with engineers and architects without needing to personally implement the solutions.\nAI Platform Knowledge\nUnderstanding of how machine learning, GenAI, RAG, and agentic AI products consume enterprise data.\nFamiliarity with concepts such as MLflow, vector search, embeddings, graph data, unstructured data, model serving, and AI data pipelines is preferred.\nAbility to identify where AI teams need reusable platform capabilities versus application-specific capabilities.\nKey Behaviors of a Successful Candidate\nDriving Success: Takes ownership of product decisions, priorities, outcomes, and the success of platform consumers.\nTechnical Curiosity: Develops enough depth in Databricks, data engineering, and AI architecture to effectively challenge assumptions, understand tradeoffs, and make informed product decisions.\nProduct Thinking: Approaches the platform as a product rather than a collection of infrastructure projects, balancing consumer experience, reuse, scalability, adoption, and enterprise value.\nImprovement Mindset: Continuously evaluates platform friction, adoption barriers, engineering feedback, and emerging technologies to identify opportunities for improvement.\nWinning Together: Builds strong partnerships across Product, Engineering, Architecture, Governance, Security, Data, Analytics, and AI teams and communicates informed perspectives constructively.\nWhy Join The Standard?\nWe have built an enduring legacy of stability, financial strength and exceptional customer service through the contributions of the service-oriented people who choose to work at The Standard. To ensure we can attract and retain the best talent, when you join The Standard you can expect:\nA rich benefits package including medical, dental, vision and a 401(k) plan with matching company contributions\n\nAn annual incentive bonus plan\n\nGenerous paid time off including 11 holidays, 2 wellness days, and 8 volunteer hours annually - PTO increases with tenure\n\nA supportive, responsive management approach and opportunities for career growth and advancement\n\nPaid parental leave and adoption/surrogacy assistance\n\nAn employee giving program that double matches your donations to eligible nonprofits and schools\n\nIn addition to the competitive salary range below, our employee-focused benefits support work-life balance. Learn more about working at The Standard.\nEligibility to participate in an incentive program is subject to the rules governing the program and plan. Any award depends on a variety of factors including individual and organizational performance.\n\nThe actual compensation for this role will be based on a combination of education and experience, knowledge and skills, position budget, internal equity, and market data.\nSalary Range:\n$109,750.00 - $186,500.00Positions will be posted for at least 5 days from original posting date.\nStandard Insurance Company, The Standard Life Insurance Company of New York, Standard Retirement Services, Inc., StanCorp Mortgage Investors, LLC, StanCorp Investment Advisers, Inc., and American Heritage Life Insurance Company and American Heritage Service Company, marketed as The Standard, are Affirmative Action/Equal Opportunity employers. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, national origin, gender identity, sexual orientation, age, disability or veteran status or any other condition protected by federal, state or local law. Except where precluded by state or federal law, The Standard will consider for employment qualified applicants with arrest and conviction records pursuant to the San Francisco Fair Chance Ordinance. The Standard offers a drug- and alcohol-free work environment where possession, manufacture, transfer, offer, use of or being impaired by an illegal substance while on The Standard's property, or in other cases which the company believes might affect operations, safety or reputation of the company is prohibited. 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