Top Senior Data Engineer Jobs in Boise, ID

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

Design, build, and optimize distributed query solutions using Starburst/Trino. Enable secure, governed data access across cloud and on-premises sources, implement data federation and query optimization, support IAM and governance in a federal environment, develop backend services and CI/CD, and troubleshoot performance in cloud-native systems.

As Lead Data Engineer, you will guide a team, manage the data platform, and oversee the development of ML infrastructure and feature stores.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

The Senior Quantitative Data Engineer will build and maintain scalable data pipelines for quantitative investment research, ensuring data integrity and compliance, while collaborating with various teams for data architecture and product strategy.

The Data Engineer at Netflix builds systems for efficient data processing and modeling, collaborating with various teams to empower analytical insights and product features.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

The Senior Data Engineer at Unchained will design and implement data pipelines, integrate APIs, ensure data governance, and mentor team members while focusing on accuracy and security.

Lead design, build, and optimize scalable ETL/ELT pipelines and enterprise semantic layers on Snowflake. Develop semantic models, implement data quality, performance tune queries, automate maintenance, enable analytics self-service, and enforce governance while mentoring engineers and collaborating with cross-functional stakeholders.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

As a Senior Data Engineer, you'll design and implement a Snowflake-centric data architecture, operationalize ML and LLM processes, and enable advanced analytics while collaborating with cross-functional teams.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Design and build Spark ETL pipelines on an AWS data platform, collaborate with stakeholders to deliver reliable large-scale data products, optimize and maintain data infrastructure, ensure data quality/governance, and manage platform operations and incident response.

Lead and scale the data analytics function, manage a distributed analytics team, deliver actionable insights, and oversee analytics projects.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

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.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.