Analytics Engineer Remote Jobs in Idaho (US)
This page tracks remote analytics engineer openings that are location-eligible for Idaho.
This page tracks remote analytics engineer openings that are location-eligible for Idaho.
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547
Hiring companies this week
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$92,000 - $330,000
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547 Jobs
426 Companies
Role Description - Work directly with startup clients as their go-to analytics partner, joining a small weekly client meeting window and staying responsive in Slack the rest of the week. - Build and maintain activation, onboarding, and feature adoption funnels, plus cohort retention and trial-to-paid conversion tracking. - Design PQL scoring models and monitor churn, expansion, and net revenue retention. - Own event taxonomy and tracking plans across Mixpanel, PostHog, or Amplitude. - Build multi-touch attribution and channel-level CAC and LTV reporting to connect marketing spend to results. - Track funnel conversion from first touch through activation, tying usage data back to pipeline and revenue. - Write SQL against Postgres to validate data, fix tracking gaps, and build reusable dashboards clients trust. Qualifications - Comfortable owning a client relationship solo, including exec-level conversations, without a lot of oversight. - Hands on production experience with Mixpanel, PostHog, or Amplitude, ideally more than one. - Strong SQL and Postgres skills for querying, validating, and modeling data. - Real understanding of SaaS growth metrics: PQLs, activation, churn, NRR, CAC, LTV. - A track record of turning ambiguous client asks into clean tracking plans and measurement frameworks. - Comfortable with startup pace and some ambiguity, since client priorities can shift week to week. - Reliable follow through on a flexible, part-time schedule with fast Slack turnaround. Requirements - Bonus points: multi-touch attribution tooling, dbt or a modern data stack, prior agency or consultancy experience, and interest in growing this into a bigger role as the client base scales.
Role Description At Life360, we collect a lot of data: 60 billion unique location points, 12 billion user actions, 8 billion miles driven every single month, and so much more. As a Senior Analytics Engineer, you will be responsible for transforming this wealth of data into trusted, well-modeled datasets that power analytics, reporting, and data science initiatives across the organization. You should have a strong foundation in data modeling, SQL, and Python, deep understanding of business metrics, and a passion for making data accessible and understandable to stakeholders at all levels. Beyond modeling and analytics engineering, you will take on some data engineering responsibilities, working directly within our Databricks-based platform to help build and maintain the pipelines that feed the datasets you model. Qualifications - Minimum 5+ years of experience in analytics engineering, data modeling, or similar roles working with enterprise-scale data. - Experience using AI/LLM coding assistants (for example, GitHub Copilot, Cursor, or Claude Code). - Expert-level SQL skills with deep understanding of query optimization and performance tuning. - Extensive experience with dbt (data build tool) including testing, documentation, and package management. - Strong programming skills in Python for data manipulation, automation, and custom analytics workflows. - Strong understanding of dimensional modeling, star schemas, one big table, and other data modeling methodologies. - Working knowledge of the Databricks platform, including SQL Warehouses, Delta Lake, and Unity Catalog. - Familiarity with orchestration frameworks and how analytics transformations are scheduled within broader data workflows. - Experience working with version control systems (Git) and implementing CI/CD for analytics code. - Strong business acumen and ability to translate business requirements into well-designed data models. - Prior experience working with advertising, ad tech, or media data is preferred. - Understanding of data governance, privacy, and compliance requirements (GDPR, CCPA, and SOX). - Familiarity with BI tools (Tableau, Looker, Mode, or similar) and how analysts consume data. - Strong ownership mindset with a passion for deeply understanding ambiguous business problems and translating them into clean, maintainable, and well-tested data models. - Excellent communication skills with ability to explain technical concepts to both technical and non-technical audiences. - Dedication to data quality, documentation, and empowering others through self-service analytics. - Bachelor's degree or equivalent experience in Computer Science, Information Security, or a related field. Requirements - Design and implement robust dimensional and relational data models that support analytical use cases across Product, Marketing, Operations, and Finance. - Build and maintain scalable dbt transformation pipelines, ensuring high data quality, performance, and cost-efficiency from raw ingestion to business-ready outputs. - Own the transformation and modeling of curated (Silver/Gold) datasets, ensuring clear contracts and traceability from raw to business-ready data. - Partner with data engineering to build and maintain data pipelines and Delta Lake tables within Databricks. - Collaborate with data analysts, product analytics, data scientists, and business stakeholders to translate requirements into durable data products. - Implement data quality tests, monitoring, SLAs, and alerting to ensure reliability of critical analytical datasets. - Enhance our LLM development support capabilities – creating tools/skills/agents that give our LLMs more context. - Partner with Data Engineers to define and enforce data contracts, ensuring schema stability and minimizing downstream breakage. - Establish and evangelize analytics engineering best practices, including version control, code review, testing standards, and documentation. - Empower self-service analytics by building intuitive, well-documented data marts and semantic layers. Benefits - Competitive pay and benefits. - Medical, dental, vision, life and disability insurance plans (100% paid for US employees). - 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees. - Employee Assistance Program (EAP) for mental wellness. - Flexible PTO and 12 company-wide days off throughout the year. - Learning & Development programs. - Equipment, tools, and reimbursement support for a productive remote environment. - Free Life360 Platinum Membership for your preferred circle.
Role Description We are seeking an experienced MDM ETL Specialist / Developer to provide technical development and hands-on delivery and support for Master Data Management services supporting the Health and Human Services Innovation Incubator project. This role will focus on Informatica MDM, Informatica PowerCenter, data integration, data quality, data governance, and analysis capabilities that support a unified cross-agency client/member view across State programs. - Use Informatica MDM tool to combine source data from agency sources, applying numerous transformations to the data that are required, applying corrections to the source files, and adding new fields via the change request process. - Working knowledge of Informatica MDM and ability to support MDM development and operational activities. - Automate the staging of data by scheduling scripts to run at optimal times, enhancing overall system performance and efficiency. - Implementing MDM jobs by creating mappings, mapplets, sessions, and workflows. - Working with different ETL transformations, including Aggregator, Expression, Filter, Router, Sequence Generator, Update Strategy, Joiner, Rank and Source Qualifier, Lookup, and Sorter. - Scheduling and monitoring ETL/Informatica jobs in development, system testing, and production environment. - Troubleshoot post-release production support issues and develop solutions. - Developing, maintaining, and analyzing complex SQL queries and scripts used to create data marts in Teradata. - Work directly with the QA team to support defect resolution, validation, and testing of MDM-related processes. - Participating in project discussions to document and recommend alternative technical solutions or requirements. - Participating in unit, integration, and system testing. Qualifications - 5+ years of experience in MDM, ETL/ELT, data engineering, or data integration development. - 3+ years of hands-on Informatica MDM implementation experience. - Experience developing ETL mappings, mapplets, sessions, workflows, transformations, scheduling, monitoring, and troubleshooting Informatica jobs. - SQL experience, with large MDM and DBMS enterprise relational platforms. - Experience with data quality, matching, unique client/member identifier, standardization, reconciliation, and data governance concepts. - Experience supporting ETL/MDM operations, performance tuning, issue resolution, and SDLC delivery. - Experience with Python programming for scripting, automation, testing, or data processing support. - Bachelor’s degree in computer science, Data Analytics, Information Systems, Engineering, or equivalent experience. Preferred Qualifications - Experience working in other MDM tools including Cloud-native MDM solutions. - Experience working in State Government, public sector, or regulated environments. - Experience with Agile/Scrum Sprint development and iterative/incremental delivery. - Experience with healthcare, Medicaid, claims, eligibility, provider, or Health and Human Services data. - Exposure to interoperability formats such as X12, EDI, XML, JSON, APIs, or HL7/FHIR. - Exposure to cloud data platforms or modernization initiatives such as Azure, ADF, Databricks, Snowflake, Data Lake, or comparable technologies is a plus. - Experience with on-prem-to-cloud migration, MDM modernization, or EDW / ETL modernization initiatives. - Exposure to automation, AI/ML, GenAI, or LLM-assisted engineering for development, testing, documentation, profiling, or data quality is a plus. - Ability to operate in a telecommute environment and matrix organization with minimal direction. Work Environment This is a remote position.
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• Own delivery and execution • Lead delivery across data initiatives, ensuring roadmaps are executed on time, at high quality, and aligned to business goals • Lead and grow the data organization • Manage and mentor data analysts and data engineers • Set technical direction and raise the bar for analytics, data modeling, and insights • Turn data into decisions • Drive advanced analysis using Python and SQL to uncover trends and influence product, customer experience, and strategy • Build and scale data infrastructure • Own data pipelines and analytics architecture using dbt and Amazon Redshift • Ensure performance, reliability, and scalability as the company grows • Ensure data trust and quality • Define and enforce data quality, validation, and governance standards • Build confidence in analytics and reporting across the organization • Partner cross-functionally • Work closely with Product, Marketing, Customer Support, and Engineering to align data efforts with real business needs • Promote modern data engineering practices • Foster a culture of learning, continuous improvement, and innovation
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• Partner directly with our stakeholders (e.g., Data Scientists, Product Managers, Designers, Engineers) on data, metrics & analytics initiatives • Lead end-to-end development of analysis and tools used by your direct stakeholders and a diverse set of teams across the company • Responsible for analyzing and interpreting data to provide valuable insights and recommendations to enhance the member experience and improve product performance • Collaborate with the data engineering and data science teams to ensure data quality, integrity, and availability for analysis • Drive the direction and execution of your work, which spans from developing scrappy analysis and tools to designing scalable systems
AHI agilon health, inc. Remote - USA Location: Columbus, OH Pay Range: $100,000.00 - $122,600.00 Salary range shown is a guideline. Individual compensation packages can vary based on factors unique to each candidate, such as skill set, experience, and qualifications.
Role Description Essential Job Functions: - Design, develop, and maintain scalable data models that support enterprise reporting, analytics, and operational decision-making. - Build, optimize, and maintain robust ETL/ELT pipelines using modern data transformation frameworks. - Develop and maintain curated datasets that improve data accessibility, consistency, and usability across business domains. - Partner with business stakeholders to gather requirements and translate business needs into scalable analytical solutions. - Lead efforts to improve data quality through validation, testing, monitoring, and implementation of data governance best practices. - Monitor and troubleshoot production data pipelines, proactively identifying and resolving performance or reliability issues. - Develop reusable SQL and Python-based solutions to automate data transformations and reporting processes. Other Job Functions: - Understand, adhere to, and implement the Company's policies and procedures. - Build collaborative relationships with business and technical stakeholders across the organization. - Drive continuous improvement by identifying opportunities to automate, standardize, and optimize analytics workflows. - Communicate technical concepts effectively to both technical and non-technical audiences. - Demonstrate accountability, initiative, and ownership of project deliverables. - Stay current with emerging technologies and industry best practices in analytics engineering and healthcare analytics. - Support cross-functional projects and contribute to strategic enterprise analytics initiatives. Qualifications - Minimum Experience: 4–7 years of experience developing analytics solutions, data transformation pipelines, or enterprise reporting platforms. - Advanced proficiency in SQL, including performance optimization and complex query development. - Strong proficiency in Python or similar programming language for data transformation and automation. - Experience designing and maintaining dimensional data models and curated analytical datasets supporting Medicare Advantage, value-based care, population health, or healthcare operations. - Experience working with modern ETL/ELT methodologies and production data pipelines. Requirements - Preferred Experience: Experience with cloud data platforms such as Snowflake, SQL Server, or similar modern data warehouses. - Strong experience with DBT or comparable data transformation frameworks. - Experience using VS Code, Git/Bitbucket, and CI/CD development practices. - Experience implementing automated data quality testing and monitoring. - Experience mentoring junior team members and participating in technical design discussions. Education - Bachelor's degree in Mathematics, Computer Science, Statistics, Engineering, Information Systems, or a related field required. - Master's degree preferred but not required. Skills and Abilities - Strong ability to translate complex business requirements into scalable and maintainable data models. - Advanced SQL development and query optimization skills. - Strong understanding of dimensional modeling, data warehousing principles, and modern analytics engineering practices. - Experience designing reliable, scalable, and well-documented data pipelines. - Strong analytical and problem-solving abilities with excellent attention to detail. - Ability to independently prioritize multiple projects in a fast-paced environment. - Excellent written and verbal communication skills with the ability to communicate effectively across technical and business audiences. - Ability to mentor junior engineers and contribute to team technical growth. - Passion for continuous learning and improving healthcare through data and analytics. Compensation The posted salary range reflects the anticipated base salary hiring range only. Final compensation will be based on experience, expertise, location, internal equity, and business needs. Candidates with exceptional experience may be considered within the broader compensation range, where appropriate. Location: Remote - MA Pay Range: $100,000.00 - $122,600.00 Salary range shown is a guideline. Individual compensation packages can vary based on factors unique to each candidate, such as skill set, experience, and qualifications.
• Own Gold-layer design and delivery, including facts, dimensions, domain data marts, and governed KPI implementations on Databricks. • Build and maintain the enterprise semantic layer through curated views, governed semantic models, metric definitions, and reusable patterns for trusted business consumption. • Translate approved KPI and metric definitions into precise, testable, auditable transformation logic that matches agreed business meaning. • Define and enforce the promotion path from domain Gold to enterprise Gold, ensuring shared metrics are not published without required business and governance sign-off. • Partner directly with business stakeholders across domains to clarify KPI definitions, challenge ambiguity, and resolve competing definitions before implementation. • Enable domain teams by creating modeling standards, reusable design patterns, review processes, and coaching mechanisms rather than acting as the long-term owner of every downstream use case. • Review Gold-layer models created by other teams or partners for correctness, definition integrity, usability, and conformance to enterprise standards. • Optimize Gold-layer structures for BI and self-service analytics consumption while preserving traceability, governance, and metric consistency. • Ensure semantic models, tables, columns, ownership, and business definitions are documented and discoverable. • Apply awareness of data sensitivity, classification, and approved use when designing joins, dimensions, semantic views, and access patterns so the semantic layer reflects both business meaning and compliance requirements.
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• Design and implement complex data models to enable dashboards, self-serve analytics, and data science teams. • Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses. • Enable AI tooling with semantic layers and observability, guiding analytics functions on best practices. • Manage and improve data infrastructure needed to drive data-driven decision-making solutions. • Help develop front end applications to expose analytical data sets enterprise wide • Work with the Product and Corporate Engineering system teams to structure source systems for reporting consumption across the enterprise.
Role Description Provide workforce metrics to HR Business Partners and COEs to translate talent data to actionable business insights. Drive Inclusion & Diversity roadmap success by identifying organizational gaps and measuring initiative impact. Optimize talent initiatives to boost retention, engagement, and organizational performance. Enable the success of Talent Acquisition initiatives and highlight the insights around Employment value proposition, hiring trends and workforce planning. Partner with Head of People Analytics to support employee surveys and executive summaries. Correlate with IT to build talent dashboards and drive adoption at various levels of the organization. Telecommuting is permitted. Wage $137,000.00 - $167,000.00 per year. Qualifications - Master’s or foreign equivalent degree in Human Resource Information Systems, Statistics, Information Systems, Industrial-Organizational Psychology, or a related field. - Must have work/internship experience or completed graduate coursework/research in each of the following: - Analyzing large volume and variety of data. - Analyzing data from disparate sources using Snowflake or other ETL tools. - Creating dashboards using visualization tools such as Power BI, Tableau. - Using Python and its libraries to perform report automations, generating snapshot data. - Performing sentiment analysis of exit interview surveys. - Data management tools, including Workday. - Data Quality assessment and clean up. - Applying various feedback collection methodologies by designing surveys. - Designing various analytics like Headcount or Talent acquisition metrics. Benefits - Competitive compensation. - Great benefits. - Workstyle within an environment of shared collaboration, transparency, and inclusivity. - Tools and resources to succeed in doing work that matters. - Opportunities to grow and develop. Interview Integrity To support fair and authentic hiring practices, candidates are not permitted to use AI tools (such as transcription apps, real-time answer generators like ChatGPT or Copilot, or automated note-taking bots) during interviews. These tools must not be used to record, assist with, or enhance responses in any way. Our interviews are designed to evaluate your individual experience, thought process, and communication skills in real time. Use of AI tools without prior instruction from the interviewer will result in disqualification from the hiring process. This position may require access to technology and/or software subject to U.S. export control laws and regulations, including the Export Administration Regulations (EAR). As such, applicants must be eligible to access export-controlled information as defined under applicable law. Marvell may be required to obtain export licensing approval from the U.S. Department of Commerce and/or the U.S. Department of State. Except for U.S. citizens, lawful permanent residents, or protected individuals as defined by 8 U.S.C. 1324b(a)(3), all applicants may be subject to an export license review process prior to employment.
• Serve as the ETL Developer supporting sustainment services for VA, migration of large-scale systems to the cloud, and delivery of advanced analytics, including Artificial Intelligence (AI) capabilities • Responsible for overall technical execution of all activities performed by the ETL Developers who are matrixed into Scrum Teams • Design robust ETL processes that facilitate seamless data integration from multiple sources into applications or the data warehouse • Coordinate across workstreams to ensure Scrum teams are properly staffed with the necessary resources • Peer review code written by other ETL Developers • Ensure all team members are trained on best practices and common coding guidelines, promoting knowledge sharing across the team • Perform a robust set of data integrity operations/checks throughout the ETL process (quality control, unit testing, functional testing, and system testing) • Ensure SQL validation scripts are run daily to check the status and data integrity of the overnight ETL jobs • Track the efficiency and performance of all automated processes to verify they are operating within defined timelines/service levels and they are producing high-quality/valid reports with traceability of data used to generate each report • Develop and validate ETL workflows and store the resulting ETL packages in GitHub • Track, by manual and automated means (i.e., triggers on sensing/logging systems), any notable deviations from target thresholds on availability, server load, disc I/O rates, etc. • Ensure solutions are appropriately configured, available, and accessible for users
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SQL, Python, ETL, dbt, Observability/Monitoring, Snowflake