Top Data & Analytics Jobs

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

Design, build, and manage large-scale data structures, pipelines, and ETL workflows. Integrate data for analytics and Data Science, optimize Hadoop/HDFS processes, develop data marts and models, ensure data quality and accessibility, and evaluate/adopt tooling for real-time and offline processing.

Design, build, and maintain large-scale data structures, ETL/ELT pipelines, and data marts. Integrate data from multiple sources, ensure data quality, and enable analytics and ML model integration. Leverage Hadoop/HDFS, cloud platforms, Airflow, streaming, containers, and generative AI frameworks to deliver scalable, auditable pipelines and backend services.

Design, build, and maintain data infrastructure and ETL pipelines; automate data ingestion and conversion; extract and analyze data from multiple sources; improve data governance, quality, and metadata; collaborate with analysts, data scientists, and engineers to support ML pipelines and dashboards; communicate project status to leadership.

Design, build, and maintain large-scale data structures, pipelines, and ETL workflows; integrate data for analytics and ML; collaborate with Data Science to operationalize models; ensure data quality, performance, and scalability across cloud and big-data platforms.

The Mid-Level Data Engineer will design and maintain data pipelines using Python and PySpark on Azure, ensuring data quality for analytics and reporting while collaborating with various stakeholders to translate requirements into practical solutions.

Data Engineers at Rhombus Power design and implement data infrastructure, analyze and maintain data systems, and collaborate across teams. They develop code for data processes and ensure strong client connections.

Build and manage large-scale data structures, pipelines, and ETL workflows; design databases and data marts; develop real-time and offline analytics; collaborate with Data Science to integrate models; ensure data quality and accessibility; troubleshoot, test, and optimize big data systems using Hadoop, Spark, Python/Java/Node.js and cloud components.

Design, build, and maintain scalable batch and streaming data pipelines, storage, and integrations on AWS. Own features end-to-end, write testable code, collaborate with cross-functional teams, support data scientists with semantic models, ensure data quality, and occasionally travel to customer sites for deployment and integration.

Build and maintain scalable data pipelines and architectures, perform ETL into data warehouses/lakes, enforce data governance and quality, manage databases, write optimized SQL, maintain metadata/catalogs, and produce Power BI reports using advanced DAX and Power Query.

As a Data Engineer, you'll create and maintain data pipelines, optimize data architecture, and support analytics tools for performance insights.

The Data Engineer will design and develop scalable analytics solutions using Azure Data Explorer and Power BI, modeling large datasets into insights and visualizations, while mentoring junior team members.

The Data Engineer/ETL Engineer will support cloud-based and on-prem application development, focusing on data management and analytics for defense and intelligence.

As a Data Engineer, you will architect and maintain the data systems, create pipelines and integrations, and ensure data quality for analytics and reporting.

The Data Engineer will build and scale Baseten's internal data platform, designing data models and pipelines while enabling self-service analytics and ensuring data reliability.

As an Analytics Engineer, you will create scalable solutions for data reporting, build data pipelines, and establish high data integrity standards while collaborating with multiple teams.

The role involves SQL and data analysis to troubleshoot issues, with 8+ years of required experience. Experience with C# and scripting tools is preferred.

As a Senior Forward Deployed Data Engineer, you will design and implement data pipelines for media agency clients, manage technical delivery, and ensure data security while mentoring junior engineers and communicating effectively with stakeholders.

The Data Engineer designs, builds, and maintains data pipelines and models, ensuring data quality and accessibility for analytics in healthcare.

Design, implement, and maintain scalable data infrastructure and real-time processing for analytics platforms. Migrate systems from AWS to on-prem Kafka/Spark, implement data transformations, support production, optimize pipelines, query and analyze data, and build scripts and APIs to operationalize data science work.

The Data Engineer will design, build, and scale data infrastructures, manage data workflows, optimize performance, and mentor junior engineers. Responsibilities include driving technical efforts, ensuring reliability, and documentation.

Lead design, development, and implementation of data management, ETL, data pipelines, reporting, API integrations, and automation for Head Start programs. Provide technical leadership, project management, data governance, system performance oversight, stakeholder coordination, and continuous improvement to deliver scalable, secure solutions.

The Looker Data Engineer will build and optimize data models, develop reporting solutions, and support data-driven decisions using Looker and other technologies.

As a Snowflake Data Engineer, you will design and maintain scalable data pipelines, optimize SQL transformations, and support analytics platforms, collaborating with stakeholders.

The Data Engineer will design and optimize ETL pipelines, integrate data, ensure data integrity, tune SQL queries, troubleshoot issues, and collaborate with teams to create data solutions.