Sr Analytics Engineer
Design and build reusable components and ETL pipelines to support ML model calibration and data ingestion. Model raw data into clean datasets and maintain documentation for data flow and architectural vision.
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Design and build reusable components and ETL pipelines to support ML model calibration and data ingestion. Model raw data into clean datasets and maintain documentation for data flow and architectural vision.
Build and activate company-wide data assets in Snowflake by designing efficient data models and pipelines using DBT. Collaborate with stakeholders to implement metrics and dimensions that enable self-service analysis and trusted KPI reporting.
Design, develop, and maintain scalable data pipelines, ETL processes, and data models to support business operations. Collaborate with stakeholders and data scientists to ensure data quality and implement data-driven visualizations.
The role focuses on the technical implementation of GA4 and Google Tag Manager to ensure accurate data tracking across various client properties. Responsibilities include configuring events, building Looker Studio dashboards, and troubleshooting tracking issues.
Design, build, and maintain dbt models in Snowflake to serve as reliable sources of truth for the company. Collaborate cross-functionally to align on metrics and champion the adoption of AI-assisted tools in data workflows.
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Build and manage the semantic data layer to ensure consistent business rules and data governance across the company. Act as a bridge between data infrastructure and business stakeholders to translate requirements into efficient dimensional models.
Design and develop Python-based analytical applications and data pipelines to transform complex data into actionable intelligence. Collaborate with stakeholders to build scalable software solutions, dashboards, and visualizations for operational insights.
Design, build, and maintain curated datasets and metric definitions to ensure reliable, consistent reporting across the organization. Partner with stakeholders to translate business requirements into data models while documenting logic for both human and AI-powered query tools.
Lead the design, evolution, and maintenance of complex data pipelines to ensure scalability and reliability. Translate business needs into technical modeling rules while establishing systemic quality and reliability standards.
The Senior Analytics Engineer will build complex data infrastructure using dbt and Snowflake while implementing scalable ELT pipelines and governance frameworks. They will also provide technical guidance, conduct code reviews, and mentor junior team members to ensure high-quality data solutions.
Design, build, and maintain robust ETL/ELT pipelines within an AWS-native environment while managing orchestration and data modeling. Engage directly with client stakeholders to gather requirements and provide technical advisory on data platform solutions.
You will be responsible for managing the semantic data layer and ensuring data governance to provide consistent business logic across the company. Additionally, you will collaborate with stakeholders to translate business requirements into efficient dimensional models while leveraging AI to automate data processes.
The Senior Analytics Engineer will design and maintain data structures, build integrated BI reports, and lead end-to-end analytics projects. They will also leverage AI-powered tools and MCP-enabled integrations to streamline data pipelines and train stakeholders on data self-sufficiency.
The role involves building analytical constructs in Python to support AI systems in interpreting structured datasets. You will collaborate with AI engineers to ensure seamless integration of analytical outputs into AI-driven insights.
Own and maintain key product metrics while analyzing user behavior to generate insights that shape product strategy. Collaborate with cross-functional teams to drive a culture of data-informed decision-making.
The Analytics Engineer II role will support the Executive and Athlete portfolio by designing and building data models and Power BI dashboards to solve business problems. This includes collaborating with various teams to understand data needs and translating those into effective BI solutions.
As a Lead Analytics Engineer, you'll architect the data foundation that powers strategic decisions across the organization. You'll transform raw data into trusted, reusable data products using DBT and modern data tools.
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You will build dashboards and reports on key people metrics and transform people data for analytics use cases. Collaborating closely with HR and leadership, you will provide insights to guide decision-making.
The Analytics Engineer will develop, maintain, and optimize business dashboards and reports using various BI tools. They will also perform complex data modeling, transformation, and SQL-based engineering tasks to ensure data accuracy and support reporting needs.
Design and operate real-time and analytical data pipelines using Azure Data Explorer to support enterprise reporting and decision-making. Collaborate with cross-functional teams to develop data models, ensure data quality, and create business-ready visualizations.
The Analytics Data Engineer will design, develop, and maintain scalable data pipelines and systems using Databricks and cloud tooling to support data-driven decision-making. They will also leverage advanced analytics and AI to analyze program data, identify automation opportunities, and ensure data quality through robust lifecycle processes.
The Lead Engineer administers and improves the engineering behind data warehousing systems for government and healthcare industries. They are responsible for leading data analysis, developing ETL pipelines, and ensuring system security and performance compliance.
You will architect, operate, and scale distributed data pipelines for vehicle telemetry and sensor data. Additionally, you will mentor engineering teams and integrate new data technologies to enhance system performance and observability.
You will architect and operate large-scale ETL, streaming, and distributed data pipelines for vehicle telemetry and sensor data. Additionally, you will mentor engineers and drive technical solutions for complex, scalable data infrastructure.
The Sr Staff Engineer will design, build, and maintain production-grade analytical data models and semantic layers to support business decision-making. They will also lead the development of reusable data products and provide technical mentorship to the analytics engineering team.
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Operate and extend existing analytical platform capabilities, integrations, governance controls, and self-service tooling while following established patterns. Monitor platform health, participate in on-call incident response, and document work for a clear contract handoff.
You will design, implement, and operate the underlying storage system for a general-purpose data platform with both OLAP and OLTP capabilities. Additionally, you will build scalable SaaS foundations and APIs to support AI-native data retrieval workflows.
You will design, implement, and operate the underlying storage system for a general-purpose data platform, including ingestion, query planning, and distributed execution. Additionally, you will build scalable SaaS foundations and APIs to support AI-native data retrieval workflows across the enterprise.
You will design, implement, and operate the underlying storage system for a general-purpose data platform with both OLAP and OLTP capabilities. Additionally, you will build scalable SaaS foundations and APIs to enable AI agents to retrieve enterprise data efficiently.
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