Top Data & Analytics Jobs

The Senior Data Engineer will oversee data operations, design scalable data pipelines, ensure data quality, and support cross-functional data initiatives.

Design, build, and operate a privacy-safe, cloud-based data platform supporting batch and real-time pipelines, analytics, ML/AI, governance, observability, and high pipeline reliability. Partner with stakeholders, set data engineering standards, troubleshoot production incidents, and mentor engineers.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

As a Data Engineer at MAI, you will develop and maintain data platforms, design ETL/ELT processes, ensure data quality, and collaborate with teams to optimize data utilization for analytics and ML applications.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.

The Senior Data Engineer will develop and optimize software applications and data platforms for NAVOCEANO, supporting mission-critical solutions, data pipelines, and analytics capabilities.

Design, build, and maintain ETL/ELT data pipelines and domain-oriented data products to support a Digital Thread. Ensure data quality, governance, mapping, and discoverability. Apply software-engineering practices (version control, testing, CI/CD, IaC) for production deployments. Integrate manufacturing and operational systems and prepare AI/ML-ready datasets for analytics and predictive use cases.

The Senior Data Engineer will develop data pipelines, analyze geospatial data, implement quality assurance processes, and support database synchronization with APIs, contributing to climate risk financial modeling.

The Data Engineer/Scientist extracts insights from complex data sets, optimizes algorithms, ensures data quality, develops BI solutions, and mentors junior team members.

As a Sr. Data Engineer at Lyra Health, you will build and scale core data infrastructure, design data warehouses, and create efficient data pipelines while collaborating across departments.

Responsible for utilizing Hortonworks architecture and tools such as Hadoop and Spark for data analysis and engineering tasks. Candidates should have relevant experience and may be considered for contract-to-hire roles.

The Sr. Ab Initio Data Integration Engineer will maintain ETL processes, troubleshoot performance issues, and provide documentation for the data warehouse environment.

As a Lead Data Engineer, you will architect data foundations for AI applications, lead a team, optimize data pipelines, and ensure data governance.

Design, build, and operate data services and pipelines to ingest, standardize, and deliver clinical data for product, analytics, and ML. Tune Spark workloads, enforce data quality, monitor production systems, and partner with product and engineering. Participate in on-call support.

The Senior Data Engineer will work with data tuning, big data technologies, and coordinate with technical teams and business users.

Design, build, and maintain scalable data pipelines and infrastructure on AWS, collaborating with data scientists and AI teams to support analytics and ML initiatives.

The Senior Data Engineer will work with data tuning on relational databases, utilize big data technologies, and coordinate with teams. A strong academic background and experience with large datasets are required.

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 Principal Data Engineer will lead complex data projects, design robust data pipelines, and drive architectural strategy for a scalable data ecosystem, while mentoring other engineers and ensuring the quality and usability of data solutions.

Design, build, and maintain scalable data processing pipelines and infrastructure (ETL/ELT). Implement large-scale data processing (Spark, MapReduce, Kafka), support stakeholders with analysis and reporting, ensure secure multi-region data handling, and optimize data delivery for analytics and business insights.

The Data QA Engineer is responsible for ensuring data quality through automated testing frameworks, SQL queries, and collaboration with analytics teams.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Lead and deliver enterprise data programs: design Snowflake-based data solutions, data models, ETL and warehouse applications, provide architecture direction, drive technology transformation, collaborate with stakeholders, and apply advanced analytics (ML/AI/GenAI).

Design and implement scalable, production-quality data solutions using cloud-based big data technologies. Develop and optimize Spark/Hive workflows, write code in Scala/Python/Java, perform performance tuning, participate in SDLC and agile processes, and collaborate to identify and execute improvements.

Design, build, and maintain scalable analytics pipelines and data models. Write efficient SQL, create dashboards and reports, monitor data quality, and partner with cross-functional teams. Leverage AI tools to accelerate analytics workflows and improve decision-making across the company.