320 Analytics Engineer jobs available for remote work from home. Apply for positions such as Full Stack Data & Analytics Engineer, Senior Analytics Engineer (Marketing), Senior Analytics Engineer (Marketing) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design and implement modern lakehouse architectures using Microsoft Fabric and Databricks while building performant ELT/ETL pipelines. Deliver complex Power BI reports and semantic models while acting as a trusted technical advisor to enterprise clients.
You will be responsible for designing and maintaining conversion pipelines and ensuring accurate signal delivery across various ad platforms. Additionally, you will manage GTM releases, monitor signal quality, and build custom marketing datasets to support performance optimization.
You will be responsible for designing and maintaining conversion signal pipelines and managing ad network integrations to ensure high-quality data delivery. Additionally, you will partner with marketing and product teams to optimize campaign measurement and build custom marketing datasets.
You will architect and maintain end-to-end data pipelines while ensuring the reliability and performance of BI reporting and ML platforms. Additionally, you will collaborate with cross-functional teams to define core business metrics and optimize data infrastructure for scalability.
You will design interactive Power BI dashboards and paginated reports to help commanders assess force readiness. Responsibilities include building DirectQuery models over Azure SQL and implementing complex Row-Level Security.
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The Senior Analytics Engineer will architect and maintain scalable data pipelines to support marketing sciences, growth analytics, and predictive modeling. They will bridge the gap between data engineering and growth initiatives by ensuring high-fidelity data availability for demand modeling and customer interventions.
You will own the finance data domain, ensuring data accuracy, reliability, and quality across financial models and reporting. This involves building data products, automating processes, and developing LLM agents to support finance and business teams.
You will design and implement complex data models while managing the data infrastructure to support analytics and data science teams. Additionally, you will collaborate with engineering teams to structure source systems and enable AI tooling with semantic layers.
The role involves building and maintaining data pipelines using dbt and Airflow while developing reliable data models for analytics. Additionally, the candidate will create Power BI dashboards and translate business requirements into effective reporting solutions.
You will design, build, and maintain the analytical data layer using dbt and SQL to ensure reliable decision-making. You will also collaborate with cross-functional teams to translate business requirements into clean, reusable data models and maintain high data quality standards.
The Data Analytics Engineer will design and deliver a global analytics platform while providing actionable insights through data modeling and visualization. They will collaborate with IT and business units to interpret complex data sets and drive process improvements across the organization.
The role involves designing and maintaining robust data systems, semantic layers, and dashboards to enable self-service analytics. The candidate will collaborate with stakeholders to translate business needs into actionable insights and mentor junior analysts.
The role involves designing and developing enterprise-scale BI solutions using Power BI and modern data architecture paradigms like Data Fabric. You will also be responsible for defining data products, managing data governance, and collaborating with stakeholders to enable self-service analytics.
The Analytics Engineer III will design and maintain dbt models to serve as a single source of truth for Assurance KPIs while ensuring high data quality. This role also involves building BI dashboards and partnering with business stakeholders to provide actionable insights on arbitration risk and product initiatives.
The role involves leading end-to-end analytics initiatives, setting standards for data models and pipelines, and partnering with Data Science and Product teams to solve complex monetization problems. You will also be responsible for architecting production-grade SQL pipelines and enabling self-serve analytics through high-quality dashboards.
The role involves leading end-to-end analytics initiatives, architecting production-grade SQL pipelines, and setting standards for data models and dashboards. You will serve as a senior technical leader and thought partner to Data Science and Product teams to solve complex monetization and revenue data problems.
The role involves designing and maintaining common data models for Zero Trust maturity, implementation evidence, and outcome measures. You will also develop analytics to measure capability maturity and partner with specialists to streamline data refresh and visualization workflows.
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You will own and improve monitoring, observability, and engineering standards across the data platform to ensure reliable pipeline health. Additionally, you will build internal tooling and support AI adoption to remove friction for data analysts and engineers.
You will lead end-to-end data initiatives by translating domain knowledge into infrastructure requirements and building AI-powered data products. Additionally, you will oversee the design and reliability of ETL/ELT pipelines while ensuring data quality through automated and manual testing.
You will build and maintain data pipelines, metrics, and dashboards to turn raw security data into actionable insights for leadership and product teams. Additionally, you will drive the analytics strategy for consumer risk, including device trust and authentication patterns, to quantify and prioritize security risks.
The Principal Analytics Engineer leads the development and governance of analytics engineering standards and data architecture for government clients. This role transforms complex data into reliable models to support strategic decision-making and digital experience outcomes.
You will own the data layer and design the analytics architecture, including a tiered platform for system of record, low-latency serving, and batch/ML processing. You will also be responsible for database performance, schema modeling, and implementing observability to ensure system reliability.
The Senior Analytics Engineer will shape data infrastructure, develop scalable data models in Snowflake, and promote best practices in analytics engineering. They will also collaborate with business stakeholders to deliver data solutions and provide mentorship to junior team members.
The Analytics Engineer will design AI-ready models and implement analytics solutions for the company's data and metrics platform. They will also collaborate with product and data science teams to build data products and optimize data pipelines using AI-assisted tooling.
The Lead Analytics Engineer will own the SQL and DBT layer to transform raw clinical and claims data into trusted, production-grade datasets. They are responsible for data quality ownership, including triaging alerts, designing validation monitors, and maintaining data modeling standards.
Design, develop, and optimize scalable data transformation pipelines in BigQuery while driving the migration of enterprise data warehouse workloads from Teradata. Manage the Common Data Model hub and ensure data consistency, quality, and alignment with business KPIs across the platform.
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The Senior Data & Analytics Engineer will build and maintain governed data models and semantic assets to enable domain self-service on the Databricks platform. This role involves partnering with business stakeholders to translate requirements into testable transformation logic while ensuring enterprise consistency.
You will define and own core metrics for infrastructure cost, usage, and efficiency while pioneering frameworks to measure the productivity impact of AI tooling. Additionally, you will build dashboards and narratives to communicate efficiency insights to stakeholders ranging from engineers to senior executives.
You will own the end-to-end data infrastructure, including the ClickHouse warehouse, ETL pipelines, and BI dashboards. You will proactively analyze business metrics like retention and unit economics to drive strategic decision-making across the company.
The Senior Analytics Engineer will build and scale the analytical foundation by transforming raw data into clean, trustworthy datasets for cross-functional teams. They will also own the dbt project, maintain the Snowflake data warehouse, and design semantic layers to support AI-powered initiatives.
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