Remote Data Warehouse Specialist Jobs
Remote Data Warehouse Specialist jobs are open across the U.S. in sectors like financial services, healthcare, retail, and SaaS, where distributed teams depend on clean, scalable data infrastructure. Remote-first firms, cloud-native companies, and enterprise organizations with distributed engineering teams are among the employers hiring right now, including AECOM, Alvarez & Marsal, and Olsson, across roles from junior warehouse developer to senior data warehouse architect. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 2,172+ Remote Data Warehouse Specialist jobs
JOB TITLE: Senior Data Scientist
LOCATION: Remote
DURATION: Permanent/Direct Hire
RATE RANGE: $125k - $150k
Position Summary:
You will play a leading role in improving data and analytics products and in creating new products and capabilities. This could include adding new data sources, improving our entity resolution and attribution algorithms, and turning one-off client analyses into dashboard features available to every client. It could also mean enhancing visualizations, building and automating prospecting and media mix models, and developing automated recommendations that improve client marketing and application flows. You may design algorithms that optimize ad targeting, ad creative, and website experience.
Responsibilities:
- Invent new solutions for our clients. You will model and optimize the connections and causal relationships that run from an ad's creative all the way to a customer's lifetime value.
- Take models from concept to production, then monitor and improve them as client data and ad platforms change.
- Work with large, multi-source datasets including:
- Real time event data from our data collection tag.
- System of record data from our financial institution clients.
- Click and spend data from our clients’ advertising platforms (Google, Bing, Meta, TikTok, ChatGPT, others).
- Analytics metadata from other client systems including Google Analytics and Hubspot.
- Review model outputs and metrics critically, and catch results that don't add up: unexpected shifts, implausible values, data gaps, leakage or broken assumptions. Then fix or improve the data, logic or models.
- Build, test and evaluate machine learning models for attribution, prediction, and optimization.
- Write clean, reproducible, production-quality Python that teammates can read and maintain.
- Explain findings clearly to technical and non-technical colleagues and clients.
- Learn marketing analytics methods from senior teammates and apply them to real client problems.
QUALIFICATIONS
- Problem Solving & Critical Thinking: Ability to question results, test assumptions, and find out why, with strong attention to detail in data, code, and conclusions.
- Overall Professional Experience: 5+ years of professional experience in data science, quantitative analytics, or machine learning, with a strong track record of independently delivering production-grade solutions.
- Machine Learning & Production Experience: 3–5+ years of hands-on experience designing, training, and monitoring machine learning models (e.g., regression, boosted trees, neural networks) in live production environments.
- Programming & Data Proficiency: 3–5+ years of proficiency in Python data processing and Linux, with demonstrated experience processing and analyzing large real-world datasets.
- Business Impact & Cross-Functional Delivery: 3+ years of proven success aligning technical deliverables with business goals, managing project timelines independently, and communicating complex findings effectively to executive stakeholders and clients.
PREFERRED QUALIFICATIONS:
- Experience with marketing data and ad platforms such as Google Ads and Meta Ads.
- Experience in the financial industry.
- Software engineering experience: version control (Git), testing, code review, QA, and deploying models or dashboards to production.
- Research experience.
Education:
- Master’s or Ph.D. in a quantitative discipline (Data Science, Computer Science, Engineering, Statistics, Mathematics, or a natural science), or a Bachelor's degree with 7+ years of relevant applied experience.
BENEFITS SUMMARY:
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate or annual salary only, unless otherwise stated. In addition to base compensation, full-time roles are eligible for Medical, Dental, Vision, Commuter and 401K benefits with company matching.
FAIR CHANCE POLICY:
Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation.
JOB TITLE: Senior Data Scientist
LOCATION: Remote
DURATION: Permanent/Direct Hire
RATE RANGE: $125k - $150k
Position Summary:
You will play a leading role in improving data and analytics products and in creating new products and capabilities. This could include adding new data sources, improving our entity resolution and attribution algorithms, and turning one-off client analyses into dashboard features available to every client. It could also mean enhancing visualizations, building and automating prospecting and media mix models, and developing automated recommendations that improve client marketing and application flows. You may design algorithms that optimize ad targeting, ad creative, and website experience.
Responsibilities:
- Invent new solutions for our clients. You will model and optimize the connections and causal relationships that run from an ad's creative all the way to a customer's lifetime value.
- Take models from concept to production, then monitor and improve them as client data and ad platforms change.
- Work with large, multi-source datasets including:
- Real time event data from our data collection tag.
- System of record data from our financial institution clients.
- Click and spend data from our clients’ advertising platforms (Google, Bing, Meta, TikTok, ChatGPT, others).
- Analytics metadata from other client systems including Google Analytics and Hubspot.
- Review model outputs and metrics critically, and catch results that don't add up: unexpected shifts, implausible values, data gaps, leakage or broken assumptions. Then fix or improve the data, logic or models.
- Build, test and evaluate machine learning models for attribution, prediction, and optimization.
- Write clean, reproducible, production-quality Python that teammates can read and maintain.
- Explain findings clearly to technical and non-technical colleagues and clients.
- Learn marketing analytics methods from senior teammates and apply them to real client problems.
QUALIFICATIONS
- Problem Solving & Critical Thinking: Ability to question results, test assumptions, and find out why, with strong attention to detail in data, code, and conclusions.
- Overall Professional Experience: 5+ years of professional experience in data science, quantitative analytics, or machine learning, with a strong track record of independently delivering production-grade solutions.
- Machine Learning & Production Experience: 3–5+ years of hands-on experience designing, training, and monitoring machine learning models (e.g., regression, boosted trees, neural networks) in live production environments.
- Programming & Data Proficiency: 3–5+ years of proficiency in Python data processing and Linux, with demonstrated experience processing and analyzing large real-world datasets.
- Business Impact & Cross-Functional Delivery: 3+ years of proven success aligning technical deliverables with business goals, managing project timelines independently, and communicating complex findings effectively to executive stakeholders and clients.
PREFERRED QUALIFICATIONS:
- Experience with marketing data and ad platforms such as Google Ads and Meta Ads.
- Experience in the financial industry.
- Software engineering experience: version control (Git), testing, code review, QA, and deploying models or dashboards to production.
- Research experience.
Education:
- Master’s or Ph.D. in a quantitative discipline (Data Science, Computer Science, Engineering, Statistics, Mathematics, or a natural science), or a Bachelor's degree with 7+ years of relevant applied experience.
BENEFITS SUMMARY:
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate or annual salary only, unless otherwise stated. In addition to base compensation, full-time roles are eligible for Medical, Dental, Vision, Commuter and 401K benefits with company matching.
FAIR CHANCE POLICY:
Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation.
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Find JobsRemote Data Warehouse Specialist Job Market
Who's Hiring
- AECOM48
- Alvarez & Marsal30
- Olsson20
- Lockheed Martin17
- ServiceNow15
Top Industries Hiring
- Technology & Software132
- Consulting & Professional Services67
- Insurance33
- Investment & Asset Management33
- Accounting & Auditing30
What Employers Look For
The qualifications that appear most often in remote data warehouse specialist jobs.
- Proficiency in SQL for complex querying, data transformation, and performance tuning
- Hands-on experience with at least one cloud warehouse platform such as Snowflake, Redshift, or BigQuery
- Experience designing and implementing ETL or ELT pipelines using tools like Informatica, dbt, or SSIS
- Knowledge of dimensional modeling concepts including star schemas, snowflake schemas, and slowly changing dimensions
- Bachelor's degree in computer science, information systems, or a closely related field
- Familiarity with data governance, data quality frameworks, and metadata management practices
Tips for Your Remote Data Warehouse Specialist Job Search
Apply early to remote roles that fit
Migrate Mate lists remote data warehouse specialist openings from across the U.S. in one place, so you can find roles that match your stack and apply directly without sifting through non-remote listings.
Show async documentation skills upfront
Remote data warehouse teams rely on written handoffs, documented data models, and clear schema change logs. Include examples of your documentation, whether a dbt project README, a data dictionary, or a migration runbook, so hiring managers see you can communicate without a whiteboard.
Build a public warehouse project portfolio
Remote employers can't walk a floor to see your work, so a GitHub repository with a documented dimensional model, ETL pipeline, or Snowflake schema build is the clearest proof you can deliver independently. Focus on decisions you made and why, not just the finished output.
Prepare for async technical interviews
Many remote-first companies conduct take-home SQL or data modeling assessments before any live call. Practice writing clear, commented queries and modeling solutions you can explain in writing, since your first impression is often a document rather than a conversation.
Remote Data Warehouse Specialist Jobs: Frequently Asked Questions
How do I get a remote data warehouse specialist job?
Target companies with distributed data engineering teams, since remote-first firms and cloud-native organizations are the most consistent hirers of data warehouse specialists outside an office. Remote employers screen hard for self-direction, clear async written communication, and hands-on proficiency with tools like Snowflake, dbt, Redshift, or BigQuery. A portfolio of documented warehouse builds, data modeling decisions, and ETL pipelines gives you a concrete edge over candidates who only list skills.
Which companies hire remote data warehouse specialists?
Remote data warehouse specialist roles are posted by AECOM, Alvarez & Marsal, and Olsson and others right now, based on current remote listings on Migrate Mate as of November 2026. Remote-first SaaS companies, fintech firms, healthcare analytics platforms, and large enterprises with distributed data teams are among the most active hirers for this role.
Can you get a remote data warehouse specialist job with no experience?
Yes, but remote entry-level data warehouse roles are harder to land because employers expect you to troubleshoot independently without in-person support from day one. Early-career candidates have the best shot at smaller remote-first companies or startups that need a generalist data person. Building a documented personal project, contributing to an open-source data project, or earning a cloud data platform certification gives you something concrete to show in place of work history.
Do you need a degree for remote data warehouse specialist jobs?
Not always. Many remote employers care more about demonstrated proficiency with SQL, cloud data platforms, and data modeling than a formal degree. A strong portfolio of warehouse builds, certifications in Snowflake, dbt, or a major cloud provider, and evidence of shipping clean, documented work can substitute for or outweigh a degree on a remote application.
Which industries hire the most remote data warehouse specialists?
Most remote data warehouse specialist openings sit in Technology & Software, Consulting & Professional Services, and Insurance, per current remote listings on Migrate Mate as of November 2026. These sectors rely heavily on distributed data infrastructure, making it practical and efficient for them to hire warehouse specialists who work fully remote alongside engineering and analytics teams spread across time zones.
See All 2,172+ Remote Data Warehouse Specialist Jobs
Find roles that match your experience and apply in just a few clicks.
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