Top Hybrid Data & Analytics Jobs in Boston, MA

The role involves operating and improving AI-driven data quality pipelines, managing offshore teams, and ensuring data accuracy and reliability. Responsibilities include monitoring pipeline performance, refining rules, and collaborating across teams to enhance data operations.

As a Data Engineer II at Magnite, you will build and optimize data pipelines with Apache Spark and Python, collaborate on data architecture, ensure operational performance, and work on infrastructure provisioning using Terraform and AWS.

Lead the development of scalable data platforms and analytics systems, overseeing teams in building data pipelines, advanced algorithms, and dashboards for data-driven decision making.

The role leads Clinical Data & Information Sciences in drug development, ensuring data integrity, compliance, and continuous improvement while collaborating with cross-functional teams to enhance business processes and experience.

The Platform Engineer, ClickHouse administers and secures ClickHouse clusters, manages Kafka ingestion, integrates with AWS, and ensures CI/CD practices. Responsibilities include schema management, access control, and cluster health monitoring.

Manage the data architecture and strategic planning for the Sales team, optimizing processes through data and AI for targeting accounts and pricing strategies.

As a Senior Statistical Programmer, you will leverage SAS programming and CDISC standards to support clinical trials, generate reports, and collaborate with cross-functional teams.

Lead the design and evolution of the enterprise data platform, establish standards, mentor teams, and collaborate across departments to deliver high-quality data products.

The PLEXOS Modeling Consultant develops and evaluates models using PLEXOS software, collaborates with teams on modeling strategies, translates data into visual formats, and communicates findings to clients, promoting solutions to energy-related issues.

The Analytics Engineer will build and maintain the semantic layer of data, ensuring reliable metrics, orchestrating ETL processes, and implementing compliance for PHI data in a healthcare setting.