Top Remote Analytics Jobs in Huntsville, AL

Provides hands-on technical leadership for data analytics support across enterprise customers. Responsibilities include resolving complex SQL, cloud platform, ELT, data pipeline, data warehouse, and BI issues; optimizing analytics solutions; conducting root cause analysis; reviewing SQL and BI changes; mentoring analysts; automating support processes; and advising customers on Tableau, Power BI, and modern analytics architecture.

Establish and lead the People Analytics function, building trusted workforce data foundations, governance, privacy standards, analytical products, workforce planning capabilities, and AI-enabled decision support. Partner across HR, Finance, IT, and business leadership to deliver executive insights, improve workforce decisions, and scale analytics operations. Recruit and develop the analytics team while ensuring responsible data use, global-local compliance, stakeholder adoption, and alignment with organizational priorities.

Design and implement scalable analytics/data models and dbt pipelines, manage Databricks, build dashboards and BI solutions, partner with business stakeholders, support CRM/marketing analytics, and explore GenAI/ML opportunities to deliver reliable, automated data products.

Consult with financial institutions to analyze consumer credit and loan performance, evaluate underwriting and decision rules, develop data-backed lending recommendations, produce client reports/dashboards, and lead engagements using MeridianLink decisioning platforms and BI tools.

Leads claims analytics by partnering with business leaders, developing reporting and data infrastructure, integrating insurance data, and delivering insights for Claims, Finance, Actuarial, and Underwriting. Creates dashboards and analyses, responds to ad hoc requests, interprets financial and actuarial reporting, and mentors junior analysts. Requires advanced SQL, BI, Power BI, and insurance industry expertise.

Build and own commercial data models in Snowflake and dbt for ARR, bookings, pipeline, account scoring, ICP fit, upsell, and whitespace analysis. Establish semantic layers, governance, documentation, testing, monitoring, and CI/CD practices. Partner with Sales, Marketing, Finance, and enterprise data teams to deliver trusted self-service analytics, improve data infrastructure, and develop AI-powered automation. This senior individual contributor will own the roadmap and mentor analysts on data modeling and dbt.

Analyze healthcare, financial, and utilization data to identify inefficiencies, support data-driven decisions, maintain dashboards, build analytical models, communicate insights, and monitor improvement initiatives across the organization.

Own client relationships and analytics strategy across digital measurement and GEO initiatives. Architect, audit, and QA GA4 and Adobe Analytics implementations; develop measurement frameworks, dashboards, experimentation plans, and causal analyses. Present insights to executive stakeholders, manage analytics workstreams, mentor teammates, and build AI-assisted workflows, automations, and scalable systems. The role combines traditional analytics with measurement of AI-powered search visibility and customer behavior.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

Build and maintain scalable ELT pipelines, dbt models, semantic layers, and governed product analytics assets. Partner with Data Engineering, Product Engineering, Data Governance, analysts, and product managers to define trusted metrics, monitor data quality, document taxonomies, and support self-service analytics. Translate product usage telemetry into certified metrics for expansion and upsell analysis, while communicating technical concepts to technical and non-technical stakeholders and driving engineering best practices.

Leads enterprise data architecture strategy, modernization, and implementation across cloud data platforms, data lakes, lakehouses, warehouses, analytics, and AI environments. Designs secure, scalable data models, ingestion and integration patterns, and cloud-native architectures. Builds prototypes, evaluates emerging technologies, guides engineering teams, and drives adoption of strategic data products. Partners with executives, business stakeholders, architects, security, and delivery teams to establish enterprise data practices and architectural direction.

Lead end-to-end analytics for Netflix Ads demand, including media planning and campaign management tools, machine learning models, and agentic solutions. Partner with scientists, product managers, engineers, and data engineering to develop metrics, reliable analytics data, insights, and recommendations. Independently identify risks and opportunities, shape product roadmaps, and communicate findings to technical and non-technical stakeholders.

Own Hercules’ full data stack, including ETL from third-party providers into BigQuery, data modeling with dbt and medallion architecture, semantic-layer metric definition, and self-service business intelligence in Omni. Build reliable, maintainable systems and dashboards while applying strong software architecture, API design, code quality, and AI-assisted development practices.

Build and expand the company’s analytics data stack using Looker, LookML, dbt, BigQuery, and Airbyte. Develop data models, integrate multiple business systems, create KPI dashboards, and analyze product usage, customer health, adoption, and revenue data. The role empowers business teams with self-service analytics, actionable insights, and data-informed decision-making while developing a strong understanding of business metrics.

Own marketing channel performance tracking, reporting, experimentation, dashboards, forecasting, and LTV analysis. Develop measurement frameworks, identify data issues, and translate complex findings into actionable recommendations for Marketing, Growth, Product, and Finance stakeholders. The role requires strong SQL, BI dashboarding, marketing measurement, experimentation knowledge, and effective analytical communication, with AI tools used to accelerate reporting and analysis.

Designs and maintains healthcare analytics infrastructure, production data models, semantic layers, and transformation pipelines using advanced SQL and analytics engineering practices. Integrates payer claims, EMR, clinical, attribution, quality, and operational data. Performs ad hoc analysis, defines standardized healthcare metrics, validates data quality, optimizes queries, documents data flows, and partners with clinical, operational, IT, and payer stakeholders to support value-based care and enterprise reporting.

Designs scalable data models, optimized SQL queries, analytics infrastructure, semantic layers, and data applications. Partners with data science, product, engineering, and business teams to enable dashboards, self-service analytics, reporting, and enterprise data-driven decision-making. The role also establishes analytics engineering best practices, improves developer experience, and supports secure, compliant data warehousing.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

Designs, builds, and maintains enterprise data pipelines, ETL processes, integrations, cloud data infrastructure, and complex data models. Supports analytics partners, develops data warehouse solutions, tunes SQL and database performance, troubleshoots production issues, and delivers end-to-end data engineering projects. The role collaborates with architects, analysts, developers, and business stakeholders, applies big data technologies, supports agile delivery, and mentors team members.

Deliver recurring and ad hoc commercial analytics, client reporting, performance-guarantee calculations, dashboards, and value measurement. Define and govern metrics, validate data, improve documentation and workflows, and automate repeatable processes. Partner with Client Success, Commercial, Finance, Product, and Analytics teams to translate complex questions into actionable insights, client-ready narratives, and recommendations that strengthen client relationships and inform business strategy.

Own the customer experience data foundation by designing dbt models, pipelines, data quality tests, documentation, semantic layers, dashboards, and self-service datasets. Integrate support, KYC, withdrawal, CRM, workforce management, and market resolution data into the cloud warehouse. Identify recurring support issues, communicate findings to stakeholders, and partner with data engineering on infrastructure and governance.

Build Polymarket’s CX data and analytics function, defining service and customer experience metrics, creating dbt models and reporting, and delivering actionable insights to leadership. Lead Analytics Engineers, partner with central data engineering on pipelines and infrastructure, and develop measurement frameworks for AI automation. Apply forecasting and modeling to staffing, contact drivers, and AI deflection while communicating recommendations to executive audiences.

Own Carrum Health’s dbt data mart, semantic layer, client-facing exports, and data reliability standards. Lead, coach, and hire analytics engineers while establishing testing, documentation, freshness monitoring, metadata, and governance practices. Develop Hex as a trusted self-service analytics and AI interface with PHI controls, support the Databricks migration, and translate business needs into prioritized technical work. The role requires hands-on coding, strong dbt expertise, cloud data warehousing experience, and operational data ownership.

Designs and governs scalable dbt data architecture, analytics models, testing, documentation, metadata, and semantic-layer standards. Builds agent-safe infrastructure and self-service analytics experiences in Hex, improves data quality and reliability, and partners with engineering, data science, and business teams. The role also influences roadmap decisions, mentors teammates, and develops reusable tooling and frameworks for trusted, cost-efficient cloud data products.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.