Top Data Engineer Jobs in Boise, ID

Design, develop, maintain, and optimize enterprise Tableau dashboards and BI solutions. Integrate and cleanse data from Oracle/Sybase/Big Data, tune SQL, automate Tableau extracts, manage Tableau Server on Linux, support testing, UAT, deployments, and troubleshoot data integrity and performance issues.

Design, build, and maintain scalable ETL/ELT pipelines into Snowflake, enforce data quality, optimize data models and query performance for Power BI reporting, produce documentation, and troubleshoot data issues while collaborating with stakeholders.

Design, implement, and maintain PySpark-based data reconciliation solutions for financial systems. Build matching algorithms, integrate with rules engines, process large distributed datasets, identify and resolve discrepancies, and collaborate with analysts and architects to improve data quality and governance.

Design, implement, and maintain data quality processes using cloud platforms (Azure/AWS/GCP). Collaborate with stakeholders to define standards, perform data profiling and cleansing, document issues and remediation, generate quality metrics, and support cross-functional teams to improve data architectures and integration.

Design, develop, test, and deploy high-performance Spark/Scala data processing applications and ETL pipelines using the Cloudera Hadoop ecosystem. Optimize Spark and platform performance, ensure data integrity and security, collaborate with data scientists and analysts, troubleshoot issues, and implement version control and CI/CD for Spark applications.

Design, build, and optimize PySpark applications and ETL pipelines to process large-scale datasets from SQL/NoSQL sources, data lakes, and streaming platforms. Ensure data quality, error handling, performance tuning, and collaborate with analysts, scientists, and architects to deliver scalable data solutions.

Design, implement, and maintain PySpark applications to automate large-scale financial data reconciliations. Build transformation and matching algorithms, integrate with rules engines, analyze data gaps, and collaborate with analysts and architects to ensure data quality and system resilience.

Design and develop Big Data applications using Java, Spark, and MapReduce on Cloudera/Hadoop ecosystems. Work with Hive, Impala, YARN, Kafka, and large datasets; write tests (JUnit), perform data analysis, and script in Unix/Python. Lead and manage global technology teams and follow industry best practices.

Design and implement big data solutions (Spark, Hive, Java, CDP). Analyze and consolidate disparate data sources, produce functional specifications, review data models, gather stakeholder requirements, validate implementations, support production deployments, investigate data quality and data lineage, and collaborate with technology leads to ensure data completeness and accuracy.

Design, develop, and maintain PySpark applications and ETL pipelines to process, transform, and integrate large-scale datasets from SQL, NoSQL, data lakes, and streaming sources. Optimize Spark job performance, implement robust error handling, and collaborate with data analysts, scientists, and architects using orchestration tools like Airflow or Luigi.

Lead SAP S/4HANA data migration activities: extract, map, transform, load, validate, and reconcile master and transactional data using BODS, Migration Cockpit, LSMW/BDC and HANA SQL. Support mock loads, cutover execution, defect remediation, and collaborate with functional owners to cleanse and correct source data.

Design and build cloud-based data applications and pipelines to analyze clinical data, enrich and provision datasets, and support clinical/operational processes. Mentor junior engineers, drive R&D for repeatable templates, collaborate with Product/Platform/Architecture, and prioritize source control, documentation, and simple solutions using modern data, ETL, and LLM tooling.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Technical lead on the Distribution Center data team building and scaling ETLs and data integrations using PySpark and DBT. Design robust pipelines to process large customer datasets, improve onboarding tooling, mentor engineers, manage contractors, and collaborate cross-functionally to support ML-driven grocery solutions.

Design, build, and operate large-scale data pipelines and ETL processes to normalize varied partner datasets. Lead technical decisions, mentor engineers, implement testing and monitoring, manage data warehouses/lakes, and collaborate cross-functionally to deliver robust data infrastructure that supports ML and product teams.

The Senior Data Engineer will construct and optimize data pipelines, work with cross-functional teams, ensure data quality and governance, and mentor junior engineers while leading advanced analytics initiatives.

Design, build, operate, and optimize large-scale data pipelines and foundational data products for Komodo's Healthcare Map. Improve pipeline reliability, observability, and performance; transform claims and EHR datasets; implement data quality, lineage, and monitoring; debug production workflows; collaborate with product and engineering teams; and enable downstream analytics and AI/ML use cases.

Design and implement BI solutions: build data models, automations, ETL/ELT workflows, dashboards, and ad-hoc analyses. Monitor and analyze RF/video performance using Dataminer/Qligent or similar tools. Collaborate with cross-functional teams, document requirements, and deliver actionable insights to optimize hybrid terrestrial and satellite video delivery.

The Data Engineer will build and maintain data platforms, deploy pipelines, monitor transformations, and collaborate with Data Scientists and DevOps.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Design, build, and maintain scalable batch and streaming data pipelines, improve data modeling and governance, contribute to enterprise data architecture, and collaborate with cross-functional teams to ensure reliable, high-quality data for analytics and operational use.

Design, build, and maintain scalable data systems and ETLs on GCP; connect production data to business systems; generate analytics and ML-driven insights for GTM teams; work cross-functionally and introduce modern tools (Airflow, DBT, Presto, Hightouch).

Design, build, and operate secure, scalable cloud-native data platforms (lakehouse/data mesh) supporting batch, streaming, ML, GIS and operational workloads. Lead ingestion/transformation pipelines, distributed processing (Spark/Kafka), data governance, observability, and mentor teams while ensuring compliance in regulated environments.

Support and maintain clients' Azure data platforms and Power BI environments. Design and deploy data pipelines, models, and analytics solutions using Microsoft stack (ADF, Synapse, Databricks, SSIS/SSAS/SSRS). Troubleshoot incidents, communicate with clients, manage licensing, document environments, and promote best practices while collaborating with stakeholders and continuous skill development.

The Data Engineer I will build and maintain data pipelines, contribute to platform code, and integrate data sources while growing alongside senior engineers in a production-focused role.