Top Analytics Engineer Jobs

Design, build, and maintain dbt-based analytics-ready data models and curated data marts powering a PBM financial risk engine. Onboard and optimize claims, pricing, contract, and utilization data, implement data quality controls, support forecasting and risk metrics, and enable advanced analytics and ML operationalization for finance and underwriting stakeholders.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

The Adobe Analytics Developer will design analytics solutions, ensure data collection across platforms, govern data layers, and lead technical efforts in analytics implementations.

The Analytics Engineer at Weedmaps will build and maintain data pipelines and analytics frameworks, collaborating with various teams to drive data-informed decision-making and improve business performance.

As an Analytics Engineer, you will develop data pipelines, analytics frameworks, and dashboards to support data-driven decisions and enhance customer acquisition. Collaborate with various teams to transform business needs into scalable data solutions while ensuring data integrity and quality.

Seeking an Analytics Engineer to design and maintain data models in Snowflake, collaborate across teams, and optimize data structures for analytics-driven decisions.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

The Staff Analytics Engineer will establish a data foundation aiding various teams at Kit by refining reporting models, ensuring consistent metric definitions, and enhancing stakeholder self-service capabilities.

The Analytics Engineer will build reliable data models, manage ETL workflows, and support Sales and Customer Success with actionable insights from data. Responsibilities include creating dashboards, designing metrics, and owning data pipelines and quality testing.

The Principal Data Analytics Engineer will design complex data models, optimize querying processes, mentor team members, and ensure data quality across financial datasets.

The Data Analyst will build data pipelines, analyze complex datasets, and provide insights to support decision-making across multiple stakeholders in GFiber.

Develop and maintain defensive countermeasures for the enterprise by analyzing data trends, coordinating cybersecurity operations, and tuning detection rules.

As an Analytics Engineer, you will transform raw data into reliable insights, build data models, and conduct analysis to support product and business decisions.

The Senior Analytics Engineer will optimize and manage data processes, mentor team members, and enhance data literacy across the organization.

The Junior Business Analytics Developer will analyze data, develop solutions, and support government clients in optimizing financial and data management processes.

Develop and implement scalable data solutions, automate workflows, build databases and applications, perform data mining, NLP, and machine learning on structured and unstructured data, create dynamic visualizations and reports, write queries and ETL pipelines, and consult with government stakeholders to improve data-driven decision making and processes.

The Data and Analytics Engineer will build and maintain scalable ELT pipelines, leveraging data for analytics and reporting within the Snowflake data architecture.

Build and maintain scalable People Analytics data pipelines and models using SQL, Python, Snowflake, and dbt. Monitor and automate ETL, implement testing, support reporting and dashboards (e.g., Looker), partner with HR/Finance/Payroll, and contribute to tooling, automation, and AI/LLM initiatives to ensure data quality and reliability.

The Analytics Engineer will build and maintain scalable data pipelines for People Analytics, partnering with various teams and ensuring data integrity and operational reliability.

The Analytics Engineer will develop scalable data pipelines, maintain data models, and build dashboards to support People Analytics initiatives, collaborating with HR and finance teams.

Build and maintain scalable People Analytics data pipelines and models using SQL, Python, Snowflake, and dbt; automate testing and orchestration; deliver dashboards and support cross-functional HR, Payroll, and Finance reporting.

Build and maintain scalable People Analytics data pipelines and models using SQL, Python, Snowflake, and dbt. Monitor pipelines, implement automated tests, create dashboards in Looker, and partner with HR/Finance to ensure data quality, automation, and delivery of analytics solutions.

Build and maintain scalable SQL and Python ETL pipelines, manage Snowflake/dbt data models, implement automated testing and monitoring, create dashboards in Looker, and partner with HR, Finance, and IT to deliver reliable People Analytics solutions and AI/LLM tooling.

Design, build, and maintain data models, pipelines, and visualizations to support personalization for Sportsbook. Collaborate with data scientists, engineers, and stakeholders to create features, ensure data quality, optimize performance, and deliver actionable analytics and dashboards.

Design, build, maintain, and optimize data models, pipelines, and visualizations to support personalization for Sportsbook. Collaborate with data scientists, engineers, and stakeholders to create features, ensure data quality, improve metric pipelines, and deliver dashboards and actionable insights.