Top Data & Analytics Jobs

The Senior Data Engineer designs, develops, and operates data pipelines for analytics and AI, ensuring data quality and collaboration with stakeholders.

The Staff Data Engineer will lead the architectural design and implementation of a compliant data platform, collaborating with multiple teams to ensure scalability, reliability, and security.

Responsible for assessing and improving data quality. Collaborates with developers to implement data logic, conducts quality reviews, and communicates issues to resolve data quality problems. Provides support to ETL teams and manages customer requirements throughout the project lifecycle.

The Stack Data Analysis Engineer monitors and analyzes critical component data, develops engineering tools, and collaborates with teams to improve product yield and quality metrics.

The Senior Data Engineer will design and optimize data services and pipelines, manage data quality, and collaborate with cross-functional teams to enhance data-driven decision-making.

The Senior Data Engineer leads the design and optimization of scalable data pipelines for AI-driven analytics while collaborating with cross-functional teams. Responsibilities include ensuring data integrity, automation, and compliance in cloud environments, particularly on Google Cloud Platform, to enhance decision-making processes.

In this role, you will design data architecture, lead integration strategies, mentor engineers, and drive AI infrastructure for cross-division data systems.

The Data Engineer will analyze data quality, design prediction algorithms, collaborate with the engineering team, and generate business insights.

The Founding Data Engineer will build the data function from scratch, designing data models, establishing infrastructure, and creating executive-level BI dashboards to drive decisions.

The Power BI Developer/Analyst transforms data into insights by creating reports and dashboards, optimizing data models, and collaborating with stakeholders to meet business needs.

As a Senior Data Engineer, you'll build ETL pipelines, design data ingestion systems, and maintain a multi-cloud ecosystem while collaborating with Data Scientists to transform data into business insights.

The Senior Data Engineer leads complex data initiatives, designing and optimizing data pipelines, ensuring data quality, and collaborating with stakeholders for analytics solutions.

The Senior Data Engineer will optimize the data platform, build scalable data pipelines, improve data access and quality, and establish data engineering discipline within the company.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

The Contractor will design and maintain data infrastructure, optimizing data pipelines and implementing best practices for data quality and reliability. Responsibilities include developing API integrations, ETL processes, and documentation, collaborating with stakeholders to translate requirements into technical solutions.

Lead the implementation and integration of a Data Catalog solution, ensuring data governance, metadata management, and compliance across the organization.

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 manage, optimize, and expand data infrastructure for a clinical data registry, focusing on enhancing data systems and reliability while developing new capabilities.

The Analytics Engineer will design data models, build pipelines, and ensure data quality to support AI evaluation and insights.

The Data Engineer will develop data pipelines and integrations, focusing on healthcare data to enhance financial operations, ensuring efficient data handling and driving impactful solutions.

The Principal Data Engineer will design and implement scalable data platforms, lead architecture discussions, and mentor teams. Requires expertise in Azure and Databricks.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts for real-time and batch analytics. Collaborate with Data Science to operationalize models, ensure data quality, optimize Hadoop/HDFS workflows, and integrate cloud-based solutions.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts to support analytics and reporting. Integrate Data Science models into automated processes, optimize Hadoop/Spark workflows, ensure data quality and accessibility, troubleshoot systems, and recommend tooling and cloud solutions.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts; optimize Hadoop/HDFS workflows; integrate data science models; ensure data quality, accessibility, and production deployments; troubleshoot systems and recommend tooling improvements.

Build and maintain large-scale data structures, pipelines, and ETL workflows; design databases, data marts and models; integrate data science models; optimize Hadoop/Spark queries; ensure data quality and accessibility; test, troubleshoot, and recommend tooling for analytics and reporting use cases.