Top Data Engineer Jobs in Albuquerque, NM

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

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.

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 the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

Develop and optimize data pipelines for reporting and advanced analytics. Ensure data quality and create real-time processing applications. Collaborate with DevSecOps teams and enhance data management procedures.

The Data Engineer will manage data infrastructure, develop analytics frameworks, and collaborate cross-functionally to enhance customer insights and retention.

The role involves writing and deploying scripts for data collection, transforming data sets, diagnosing bugs, and collaborating with other engineers using agile principles.

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.

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

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

The Data Architect designs data flows, defines standards, ensures data quality, and collaborates on data strategies while integrating advanced technologies.

Interns will support Databricks ETL framework, improve documentation, validate Metapedia, and engage in AI/ML discovery. Requires good communication and data engineering knowledge.

This role involves building and maintaining data pipelines, developing data models, and ensuring data discoverability while enabling scalable analytics on blockchain data.

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 Senior AI Data Engineer will design and maintain datasets for AI models in cybersecurity, ensuring data quality and relevance while collaborating with teams.

As a Data Engineer, you'll design and maintain data platforms, develop data pipelines, collaborate with teams, and ensure data quality for diverse stakeholders.

The Data Engineer will manage data ingestion in Salesforce, standardize lead data, ensure data quality, and optimize integration workflows.

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

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Design and maintain high-quality data pipelines, develop DBT models, collaborate with analytics and data science teams, and optimize data operations for scalability.