Top Data Engineer Jobs in Boston, MA
As a Machine Learning Engineer at ZS, you will build and monitor model pipelines, scale ML algorithms, implement MLOps, and write production-ready code. You will ensure high quality deliverables, collaborate with client teams, and contribute to evaluating new technologies and architecture patterns.
The Senior Research Data Steward manages data and metadata for defined domains, ensuring data integrity and compliance. Responsibilities include collaborating with data owners, establishing data management plans, and promoting best practices in data governance. The role involves communicating with various stakeholders and providing training to enhance data management processes.
The R&D Head for Digital, Data, and Technology at Takeda leads the integration of AI, data, and digital technologies across R&D. This role focuses on enhancing the speed and quality of discovering, developing, and delivering innovative medicines, and manages the digital transformation efforts company-wide.
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The Senior Data Engineer (Data Engineer III) at Chewy will be responsible for designing and optimizing data systems, managing data integration and management, providing collaborative leadership, mentoring peers, implementing innovative solutions, forming strategic partnerships, and following agile practices. The ideal candidate will have a Bachelor’s or Master’s degree in a related field, 5 years of data engineering experience with a focus on cloud environments and enterprise data warehouses, expertise in SQL and Python, and strong leadership and communication skills.
The Senior Data Engineer will analyze requirements, write and ship code in dbt, design data pipelines, enhance data systems, and mentor junior engineers. This role focuses on leveraging data for strategic business impact and improving developer efficiency through automation within a cloud environment.
The Principal Business Intelligence Engineer will lead data visualization efforts, develop dashboards using Tableau, manage relationships with internal customers, and mentor junior team members. This role involves analyzing data integrity, governing datasets, and presenting analytical results to non-technical decision-makers.
The Lead Analytics Engineer will lead the development and optimization of data analytics frameworks, focusing on ETL processes, data modeling, and orchestration using tools like DBT, Snowflake, Airflow, and Dagster. Responsibilities include mentoring team members, managing multiple projects, collaborating with cross-functional teams, and championing best practices in data analytics.
The Portfolio Chief Engineer will lead the design and implementation of data and analytics systems, engaging with customers and end users to ensure solutions meet mission needs. Responsibilities include supporting technology roadmaps, optimizing solution designs, and assisting in capturing new business opportunities.
The Sr. Data Engineer-GCP designs, develops, and integrates data applications on Google Cloud Platform. Responsibilities include building data processing systems, automating data pipelines, leading unit testing, adhering to quality standards, and implementing process improvements. The role leverages machine learning and collaborates with internal and external resources to support reporting and analytics needs.
The Data Modeler will collaborate with technology and product teams to design and maintain data models for the enterprise data warehouse. Responsibilities include leading design discussions, managing data quality, guiding product teams in data model creation, and ensuring adherence to standards while facilitating stakeholder discussions.
The Geospatial Analytics Data Platform Architect will design and implement geospatial data architectures for large-scale analytics and machine learning using GCP. The role includes establishing data governance frameworks, leading cross-functional teams, and providing geospatial expertise to create innovative data solutions.
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