Remote Data Solutions Manager Jobs
Remote data solutions manager jobs are open across the U.S. in sectors like software, financial services, healthcare technology, and enterprise SaaS, where distributed data teams depend on experienced managers to align data infrastructure with business needs. Remote-first companies and large enterprises with distributed operations are among the most active hirers, posting roles from mid-level to senior and director-level positions. Employers hiring remotely right now include G2, Tempus, and Protective. Find a role that fits below and apply directly.
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Showing 5 of 55+ Remote Data Solutions Manager jobs
Section 1: Position Summary
The Director, Data Solutions leads the data foundation for Ascensus Data & Analytics: the architecture, engineering, integration and quality work that enterprise reporting, client-experience analytics and predictive modeling all depend on. The role is accountable for connecting disparate source systems into a connected intelligence layer, so insight can be drawn across the enterprise rather than one system at a time, and so analytics teams build on trusted data instead of assembling it themselves.
The Director reports to the Senior Vice President, Data & Analytics and leads a team spanning data engineering, data product management and business analysis. The role works closely with Technology on data priorities, pipeline delivery and platform standards, starting with the Retirement business line, and with analytics leaders and business stakeholders on sequencing what gets built first.
Section 2: Job Functions, Essential Duties and Responsibilities
- Data Architecture & Technical Direction: Define the target architecture for our shared data environment, including the layered (medallion) structure, semantic models and reporting layers, working with Technology and enterprise architecture. Set standards for pipeline design, source control, testing, deployment and documentation, and hold the team to them.
- Connected Data Sets & Integration: Build the integrated data sets that join sources across the enterprise. Near-term priorities include client interactions, book of business, customer experience and behavioral trends, and product and partner definitions with a reliable source of truth. Deliver the shared client-interaction source covering digital, workflows, interactions and sentiment, and the advisor data pipeline connecting core platform data with CRM sales activity.
- Process Efficiency & Automation: Automate the manual, repetitive reporting and data preparation work that consumes capacity today. Track cycle time and manual touchpoints on recurring deliverables and reduce both.
- Data Products & Roadmap: Work with the data product owner to maintain a prioritized data roadmap tied to analytics and business priorities. Build data sets once, document them, assign owners, and make them reusable across teams instead of rebuilt per project.
- Data Quality & Governance: Establish a single source of truth for enterprise reporting and client insight. Maintain enterprise data definitions so key terms mean the same thing across lines of business. Run data quality audits, and identify gaps in foundational systems that block enterprise-wide reporting and cross-sell insight.
- AI & Advanced Analytics Enablement: Structure and govern data to support predictive and propensity modeling and emerging agentic workflows, working with data science and analytics early enough that the foundation is ready when the models are.
- Technology Partnership: Act as the main point of coordination with Technology on data priorities, platform upgrades and the ongoing support model. Represent Data & Analytics requirements in architectural review and influence decisions so solutions stay consistent and scalable across teams.
- Team Leadership & Development: Lead, coach and develop a team spanning data engineering, data product management and business analysis. Set clear expectations for engineering discipline and delivery, mentor through code and design review, and build the bench as the function grows.
- Stakeholder Communication: Explain technical constraints and trade-offs in plain business terms to analytics leaders, business stakeholders and executives, and communicate status, dependencies and risk early.
General
- Proactively adopt, protect and boldly embrace emerging technologies (AI, automation, etc.), platforms, and evolving practices that accelerate transformational growth and advance Ascensus’ mission and client commitments.
- Responsible for protecting, securing, and proper handling of all confidential data held by Ascensus to ensure against unauthorized access, improper transmission, and/or unapproved disclosure of information that could result in harm to Ascensus or our clients. At Ascensus we are guided by our Core Values of People Matter, Quality First and Integrity Always®. They inspire us every day to prioritize an environment of respect for those we serve and one another and should be visible in your actions on a day-to-day.
Supervision
Section 3: Experience, Skills, Knowledge Requirements
- Leadership & Experience: 10+ years in financial services in data engineering, data management, business intelligence or systems analysis, including at least three years managing a data or reporting team.
- Process Ownership: Experience owning a recurring, deadline-driven data production cycle, such as regulatory reporting, capital planning or stress testing submissions, financial close or executive reporting, with responsibility for streamlining it over successive cycles.
- Technical Expertise: Strong SQL, including optimization of complex queries and tuning of stored procedures. Proficiency in ETL/ELT and pipeline design, dimensional and semantic modeling, and modern cloud data platforms. Experience with layered data architectures, data lineage and data quality tooling. Working familiarity with the Microsoft data stack in use at Ascensus (SQL Server, SSIS, SSAS, Power BI semantic models) is strongly preferred.
- Systems Analysis & Solution Engineering: Experience designing, developing, testing and administering internal applications and reporting tools, including replacing vendor products where an internal solution serves the business better.
- Delivery Discipline: Experience with software development lifecycle methodologies (Agile Scrum, Kanban) using tools such as Azure DevOps or Jira for requirements and delivery management.
- AI/ML Readiness: Practical understanding of what predictive, propensity and generative AI use cases require of upstream data, including structure, granularity, freshness, lineage and governance.
- Business & Industry Acumen: Retirement, wealth management, asset management, banking or fintech experience preferred. Able to connect data investments to commercial outcomes and explain the value and trade-offs of foundational work to non-technical leaders.
- Collaboration & Influence: Proven ability to build working relationships across Technology, Operations, Product and business teams, and to exercise good judgment independently. Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, Finance or a related field required, or equivalent work experience. Advanced degree or relevant data platform certifications preferred.
For all virtual remote positions, in order to ensure associates can effectively perform their job duties with no distractions, we require an uninterrupted virtual workspace and there is also an expectation of family care being in place during business hours. Additionally, there is an internet work speed requirement of 25 Mbps or better for individual use. If more than one person is utilizing the same internet connection in the same household or building, then a stronger connection is required. If you are unsure of your internet speed, please check with your service provider. Note: For call center roles specifically, it is a requirement to either hardwire your equipment directly to the internet router or ensure your workstation is in close proximity to the router. Please ensure that you are able to meet these expectations before applying.
We are proud to be an Equal Opportunity Employer
Be aware of employment fraud. All email communications from Ascensus or its hiring managers originate from @ascensus.com or @futureplan.com email addresses. We will never ask you for payment or require you to purchase any equipment. If you are suspicious or unsure about validity of a job posting, we strongly encourage you to apply directly through our website.
Section 1: Position Summary
The Director, Data Solutions leads the data foundation for Ascensus Data & Analytics: the architecture, engineering, integration and quality work that enterprise reporting, client-experience analytics and predictive modeling all depend on. The role is accountable for connecting disparate source systems into a connected intelligence layer, so insight can be drawn across the enterprise rather than one system at a time, and so analytics teams build on trusted data instead of assembling it themselves.
The Director reports to the Senior Vice President, Data & Analytics and leads a team spanning data engineering, data product management and business analysis. The role works closely with Technology on data priorities, pipeline delivery and platform standards, starting with the Retirement business line, and with analytics leaders and business stakeholders on sequencing what gets built first.
Section 2: Job Functions, Essential Duties and Responsibilities
- Data Architecture & Technical Direction: Define the target architecture for our shared data environment, including the layered (medallion) structure, semantic models and reporting layers, working with Technology and enterprise architecture. Set standards for pipeline design, source control, testing, deployment and documentation, and hold the team to them.
- Connected Data Sets & Integration: Build the integrated data sets that join sources across the enterprise. Near-term priorities include client interactions, book of business, customer experience and behavioral trends, and product and partner definitions with a reliable source of truth. Deliver the shared client-interaction source covering digital, workflows, interactions and sentiment, and the advisor data pipeline connecting core platform data with CRM sales activity.
- Process Efficiency & Automation: Automate the manual, repetitive reporting and data preparation work that consumes capacity today. Track cycle time and manual touchpoints on recurring deliverables and reduce both.
- Data Products & Roadmap: Work with the data product owner to maintain a prioritized data roadmap tied to analytics and business priorities. Build data sets once, document them, assign owners, and make them reusable across teams instead of rebuilt per project.
- Data Quality & Governance: Establish a single source of truth for enterprise reporting and client insight. Maintain enterprise data definitions so key terms mean the same thing across lines of business. Run data quality audits, and identify gaps in foundational systems that block enterprise-wide reporting and cross-sell insight.
- AI & Advanced Analytics Enablement: Structure and govern data to support predictive and propensity modeling and emerging agentic workflows, working with data science and analytics early enough that the foundation is ready when the models are.
- Technology Partnership: Act as the main point of coordination with Technology on data priorities, platform upgrades and the ongoing support model. Represent Data & Analytics requirements in architectural review and influence decisions so solutions stay consistent and scalable across teams.
- Team Leadership & Development: Lead, coach and develop a team spanning data engineering, data product management and business analysis. Set clear expectations for engineering discipline and delivery, mentor through code and design review, and build the bench as the function grows.
- Stakeholder Communication: Explain technical constraints and trade-offs in plain business terms to analytics leaders, business stakeholders and executives, and communicate status, dependencies and risk early.
General
- Proactively adopt, protect and boldly embrace emerging technologies (AI, automation, etc.), platforms, and evolving practices that accelerate transformational growth and advance Ascensus’ mission and client commitments.
- Responsible for protecting, securing, and proper handling of all confidential data held by Ascensus to ensure against unauthorized access, improper transmission, and/or unapproved disclosure of information that could result in harm to Ascensus or our clients. At Ascensus we are guided by our Core Values of People Matter, Quality First and Integrity Always®. They inspire us every day to prioritize an environment of respect for those we serve and one another and should be visible in your actions on a day-to-day.
Supervision
Section 3: Experience, Skills, Knowledge Requirements
- Leadership & Experience: 10+ years in financial services in data engineering, data management, business intelligence or systems analysis, including at least three years managing a data or reporting team.
- Process Ownership: Experience owning a recurring, deadline-driven data production cycle, such as regulatory reporting, capital planning or stress testing submissions, financial close or executive reporting, with responsibility for streamlining it over successive cycles.
- Technical Expertise: Strong SQL, including optimization of complex queries and tuning of stored procedures. Proficiency in ETL/ELT and pipeline design, dimensional and semantic modeling, and modern cloud data platforms. Experience with layered data architectures, data lineage and data quality tooling. Working familiarity with the Microsoft data stack in use at Ascensus (SQL Server, SSIS, SSAS, Power BI semantic models) is strongly preferred.
- Systems Analysis & Solution Engineering: Experience designing, developing, testing and administering internal applications and reporting tools, including replacing vendor products where an internal solution serves the business better.
- Delivery Discipline: Experience with software development lifecycle methodologies (Agile Scrum, Kanban) using tools such as Azure DevOps or Jira for requirements and delivery management.
- AI/ML Readiness: Practical understanding of what predictive, propensity and generative AI use cases require of upstream data, including structure, granularity, freshness, lineage and governance.
- Business & Industry Acumen: Retirement, wealth management, asset management, banking or fintech experience preferred. Able to connect data investments to commercial outcomes and explain the value and trade-offs of foundational work to non-technical leaders.
- Collaboration & Influence: Proven ability to build working relationships across Technology, Operations, Product and business teams, and to exercise good judgment independently. Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, Finance or a related field required, or equivalent work experience. Advanced degree or relevant data platform certifications preferred.
For all virtual remote positions, in order to ensure associates can effectively perform their job duties with no distractions, we require an uninterrupted virtual workspace and there is also an expectation of family care being in place during business hours. Additionally, there is an internet work speed requirement of 25 Mbps or better for individual use. If more than one person is utilizing the same internet connection in the same household or building, then a stronger connection is required. If you are unsure of your internet speed, please check with your service provider. Note: For call center roles specifically, it is a requirement to either hardwire your equipment directly to the internet router or ensure your workstation is in close proximity to the router. Please ensure that you are able to meet these expectations before applying.
We are proud to be an Equal Opportunity Employer
Be aware of employment fraud. All email communications from Ascensus or its hiring managers originate from @ascensus.com or @futureplan.com email addresses. We will never ask you for payment or require you to purchase any equipment. If you are suspicious or unsure about validity of a job posting, we strongly encourage you to apply directly through our website.
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Find JobsRemote Data Solutions Manager Job Market
Who's Hiring
Top Industries Hiring
- Insurance
- Technology & Software
- Distribution & Wholesale
- Banking & Financial Services
- Consulting & Professional Services
What Employers Look For
The qualifications that appear most often in remote data solutions manager jobs.
- Five or more years of experience managing enterprise data platforms or data solutions
- Proficiency with cloud data platforms such as Snowflake, Databricks, or BigQuery
- Experience leading cross-functional teams including engineers, analysts, and data architects
- Bachelor's degree in computer science, information systems, or a related technical field
- Demonstrated ability to implement data governance frameworks and data quality standards
- Familiarity with SQL, data modeling concepts, and ETL or ELT pipeline management
Tips for Your Remote Data Solutions Manager Job Search
Apply early to remote roles that fit
Migrate Mate lists remote data solutions manager openings from across the U.S. in one place, so you can find roles that match your background and apply directly without sorting through non-remote listings mixed in.
Show async communication skills upfront
Remote data solutions manager roles depend on written clarity. Lead your resume and cover letter with examples of stakeholder documentation, decision logs, or async project updates you owned, since remote employers screen for this before the first interview.
Demonstrate cloud and BI platform fluency
Remote employers in this role prioritize candidates who can hit the ground running in tools like Snowflake, dbt, Tableau, or Looker without in-person onboarding. Name the specific platforms you have shipped solutions in, not just categories.
Prepare for remote-specific interview formats
Many remote hiring processes include an async video screen or a written case study before any live call. Practice walking through a data solution you managed in writing, covering scope, stakeholder alignment, and outcome, since that is exactly what remote interviewers are evaluating.
Remote Data Solutions Manager Jobs: Frequently Asked Questions
How do I get a remote data solutions manager job?
Target remote-first companies and enterprises with distributed data teams, since they build workflows around async communication and independent execution from day one. Remote employers screen for strong written communication, proven self-direction, and hands-on fluency with cloud data platforms, SQL, and BI tools. Demonstrating that you can manage stakeholders, document decisions clearly, and deliver results without in-person oversight gives you a concrete edge over candidates who lack remote experience.
Which companies hire remote data solutions managers?
Remote data solutions manager roles are posted by G2, Tempus, and Protective and others right now, based on current remote listings on Migrate Mate as of November 2026. These tend to be remote-first technology companies, distributed enterprise teams in financial services and healthcare, and SaaS firms where data infrastructure is central to the product.
Can you get a remote data solutions manager job with no experience?
Yes, but remote entry-level openings in this role are limited because employers expect you to work independently without close supervision from day one. Your strongest path is through smaller remote-first startups or internal transfers where you can point to data projects you owned, stakeholder problems you solved, or tools you implemented. A portfolio of concrete outcomes, even from freelance or volunteer work, opens more doors than credentials alone.
Do you need a degree for remote data solutions manager jobs?
Not always, though many remote employers list a bachelor's degree in a data, computer science, or business field as preferred. What remote hiring managers weigh most heavily is demonstrated ability to manage data solutions end-to-end, including tool selection, stakeholder alignment, and delivery. Candidates who can show a history of shipped projects, measurable results, and fluency with modern data stacks consistently compete well regardless of their educational background.
Which industries hire the most remote data solutions managers?
The sectors hiring the most remote data solutions managers are Insurance, Technology & Software, and Distribution & Wholesale, based on current remote listings on Migrate Mate as of November 2026. These industries rely heavily on distributed data teams that need managers who can coordinate across time zones, align data strategy with business goals, and deliver without requiring on-site presence.
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