Top Analytics Engineer Jobs in Austin, TX

Build and maintain production data pipelines and foundations for People Analytics and AI-driven tools. Integrate HR systems (Workday, Greenhouse), design data models, ensure governance for sensitive employee data, support data science and reporting, and deliver dashboards and Streamlit apps. Optimize queries, enable LLM consumption with quality and latency controls, and collaborate cross-functionally to transition AI prototypes to production.

The Senior Analytics Engineer will lead data initiatives, manage analytics platform roadmaps, and create reliable data models while ensuring high-quality insights for stakeholders.

Build and maintain dbt data models, design BI dashboards and reports (Count and other tools), and deliver merchant/issuer analytics. Partner with GTM and product teams to translate data into actionable insights, improve data quality, and lead technical investigations to scale analytics infrastructure.

The Senior Analytics Engineer manages end-to-end analytics delivery, focusing on dbt model development and Tableau dashboard creation while collaborating with business teams for data solutions.

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.

Design and implement a scalable Elasticsearch-based analytics platform integrated with an Oracle data warehouse. Architect data models, ingestion/CDC pipelines, index/shard strategies, and monitoring. Optimize cluster, queries, and caching for sub-second dashboard performance, perform load testing and capacity planning, and produce operational documentation and SLAs.

Build and maintain Sekai's analytics transformation layer: design canonical datasets, define company-wide metrics, implement data quality and freshness checks, support experimentation and cohort/funnel analysis, and partner with product and engineering to improve instrumentation and analytics tooling.

Develop, enhance, and support Synchrony’s metadata management and cataloging platform (Ab Initio Metadata Hub). Collaborate with governance, engineering, and analytics stakeholders to ensure metadata quality, lineage, and discoverability; design solutions, implement platform changes, test, document runbooks, and enable cloud and AI/ML metadata use cases.

Lead architecture and implementation of a large-scale analytics stack: design foundational pipelines, establish modeling/orchestration standards, integrate AI-assisted engineering tools, translate business questions into version-controlled data models, partner with stakeholders to define metrics and data contracts, migrate logic into maintainable pipelines, and optimize cloud warehouse performance for scale.

The Senior Analytics Engineer will create scalable data systems, ensure data quality, support cross-functional teams, and communicate insights effectively.

Build and maintain analytics pipelines, data models, dashboards, and analyses to measure product metrics and business outcomes. Partner with Product, Engineering, and stakeholders to define metrics, evaluate initiatives, enable self-service analytics, and establish analytics best practices for scalable, performant data systems.

Own and improve dbt models, ELT pipelines, and warehouse architecture (Snowflake or equivalent) to deliver reliable executive KPIs and metric governance. Build data spine for Finance/Operations, enforce data quality/testing, partner cross-functionally with Engineering, FP&A, and Accounting, and influence analytics engineering standards, tooling, and roadmap.

The Analytics Engineer will design, build, and maintain scalable data models, collaborating with various teams to ensure data quality and robust reporting, mainly using dbt and SQL.

The Senior Analytics Engineer will build and maintain data foundations for corporate reporting, translating business requirements into data models, ensuring consistent metric definitions and investigating data discrepancies for reliable reporting.

As a Senior Analytics Engineer, you'll design and manage data pipelines, develop reporting solutions, and provide actionable insights using data to improve healthcare delivery while collaborating across teams.

Own and improve the dbt transformation layer, semantic layer, data observability, and pipeline orchestration while migrating the platform to AWS. Ensure data quality and governance to support clinical AI, collaborate with clinical, operations, and finance stakeholders, and audit, document, and fix existing data pipelines.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

The role involves designing, developing, and maintaining integration processes using Dell Boomi or Workato, managing implementations, and collaborating with IT partners to meet client requirements.

Build and maintain electricity cost modeling REST APIs and DBT data pipelines, translate SME requirements into designs, participate in technical reviews, improve engineering processes, and collaborate across remote squads to deliver energy analytics and battery performance simulations.

Build and maintain electricity cost modeling REST APIs and DBT-driven data pipelines. Translate SME requirements into engineering designs, participate in design reviews, improve engineering practices, and deliver scalable analytics and battery performance simulations to inform DER ROI.

The role involves designing and maintaining data models and pipelines, collaborating with teams to drive insights, and building dashboards for analytics and reporting.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

The Data Engineer will build and optimize ETL pipelines, manage data integration, and develop data models to enable analytics for marketing and product insights.

The AI Developer is responsible for designing and deploying AI solutions, including autonomous agents and predictive models, and integrating them into business operations.

As a Senior Full Stack Software Engineer, you will own product features, design scalable systems, mentor teammates, and ensure coding excellence while collaborating with cross-functional teams.