Top Analytics Engineer Jobs in Boston, MA
Lead Analytics Engineer responsible for developing and optimizing data analytics frameworks and infrastructure. Key responsibilities include leadership, strategic planning, project management, technical implementation, collaboration, continuous improvement. Qualifications include experience in lead analytics roles, expert knowledge of SQL and Snowflake, experience with ETL methodologies and data modeling, proficiency in Airflow, Dagster, and GIT, and programming skills in Python.
As an Analytics Engineer at **first** hand, you will build data modeling solutions, develop data models and schemas for analysis, collaborate with stakeholders, help build data-driven processes, and enable teams to self-serve data analytics needs. You should have experience with clinical medical records, data modeling, and SQL. This is an opportunity to make a massive impact on foundational technology and shape the culture of a data-driven organization.
Klaviyo is seeking an Analytics Engineer to play a pivotal role in data engineering for Product Analytics, developing datasets and deriving insights. Responsibilities include building production datasets in SQL, managing an internal analytics platform, enabling efficient data processing, and owning the data roadmap for new product areas.
Seeking a Senior Analytics Engineer to drive technical solutions and governance for data infrastructure supporting GTM modeling and analytics. Responsibilities include developing data models, ensuring data integrity, monitoring ETL pipelines, managing data scale, and collaborating across disciplines.
The Principal Data Engineer will play a critical role within the data team by providing technical leadership, implementation expertise, and guiding other data engineers. This role involves collaborating with various teams to build an analytics platform centered around Snowflake and Tableau.
Leader Bank is looking for a Data Engineer to write and maintain data pipelines, analyze large data sets, improve data reliability, and develop analytic tools. The ideal candidate should have a Bachelor's degree in Data Engineering, experience in designing databases and analytical systems, proficiency in Python and SQL, and a passion for problem-solving.
As a Senior Data Engineer at Chewy, you will design and optimize data systems, manage data integration, provide leadership and mentorship, implement innovative solutions, build strategic partnerships, and follow agile practices. You will need a Bachelor's or Master's degree in a related field, at least 5 years of data engineering experience, expertise in SQL and Python, and strong leadership and communication skills.
Align client data strategies to their business strategy, assist in choosing a platform, define data needs, and migrate to a modern cloud data environment using various providers such as Azure, Google Cloud Platform, Amazon Web Services, Snowflake, Databricks, or Teradata.
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The Data Engineer at Arcadia is responsible for designing and building data connectors and ingestion pipelines, supporting processes like peer code reviews and sprint planning, and contributing to multiple implementations simultaneously. The role involves working on new customer setups, supporting existing customers, and collaborating with various teams to drive success in data integration projects.
Lead the design, implementation, and optimization of data architecture, warehouses, and governance policies. Collaborate with stakeholders to deliver actionable insights and support business use cases. Provide technical leadership and mentorship to data engineering teams. Stay current with emerging data technologies.
As a Senior Lead Data Science Engineer (Personalization), you will drive impactful projects to create the most relevant product in the Sportsbook industry by leveraging data science and analytics. Responsibilities include developing advanced statistical models, collaborating with cross-functional teams, ensuring data quality, and leading a team to innovate with new data-driven approaches.
As the Data Science Technical Lead for Sleep at WHOOP, you will develop and maintain algorithms for sleep tracking and analysis, collaborate with MLOps engineers, conduct research on sleep physiology, and mentor other data scientists. Bachelor's degree and 5 years of experience required.
The Data Architect will embed themselves in Data Product teams and support all aspects of data ingestion, data engineering, design, data modeling, data as a service and machine learning. Responsibilities include leading data analysis, design, implementation, and ensuring adherence to data design and security standards for new cloud data platforms and products.
Design, build, and maintain complex ELT jobs that deliver business value. Translate high-level business requirements into technical specs. Ingest data from disparate sources into the data lake and data warehouse. Cleanse and enrich data and apply adequate data quality controls. Provide insight and direction to guide the future development of MassMutual's data platform. Develop re-usable tools to help streamline the delivery of new projects.
Zone & Co is seeking a Business Intelligence Engineer with expertise in Power BI, Azure, and SQL. Responsibilities include data modeling, report creation, DAX and SQL scripting, integration, performance tuning, collaboration, and staying up-to-date with the latest trends. The candidate must have a Bachelor's degree and 3-5 years of experience in developing data models using Power BI, Power Query, and DAX.
Flipside Crypto is seeking a Data Scientist to build with us and our community. Come help Flipside create the best possible web3 data products, and contribute to our tools, research, and IP as part of our mission to help blockchains achieve their full potential.
Join our team as a Data Engineer to work on a multi-year project building a clinical data registry platform in the healthcare industry. Utilize your expertise in SQL, Python, Big Data technologies, and Cloud platforms to manage and optimize data infrastructure for critical insights.
As a Data Engineer, you will architect data solutions using modern engineering principles, ensure scalability and reliability, and optimize data processing and retrieval performance. Your role involves technical acumen, strategic thinking, and collaboration within the team and organization.
The Enterprise Data Engineer at GMO is responsible for designing and implementing SQL and Python solutions for Portfolio Management, Operations, Marketing, and Client Reporting teams. This role includes maintaining an Azure Synapse Enterprise Data Warehouse, migrating systems to a cloud environment, and supporting production data processing within the enterprise ecosystem.
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