Data Engineer

July 31

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Biofourmis

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As a global leader in digital therapeutics, we combine the power of AI with wearables data to enable personalized care.

Physiology Science • Post-acute Monitoring • Physiology Monitoring • Artificial Intelligence • Digital Health

201 - 500

Description

• We are seeking a Data Engineer with proven expertise in managing, securing, and scaling data for both internal stakeholders and external clients. • This role demands comprehensive management of data flows, including collection, cleaning, integration, and transfer, to maintain the highest standards of data quality and security. • You will be a key contributor in the US location, working closely with Data Engineer and Data Scientist counterparts in Biofourmis' US, India and Singapore locations. • Act as a key enabler for teams of architects, engineers, analysts, data scientists, and business users. • Design, implement, and manage ELT pipelines, enhancing data analysis and pipeline functionality across various product lines. • Collaborate with technical teams to enhance our data platform's capabilities, ensuring scalable, efficient operations. • Manage scalability and access controls within our BI tools, focusing on stringent security and performance standards. • Develop and maintain data schemas that support internal analytics and client data exchanges. • Resolve challenges efficiently to maintain service level agreements (SLAs) and ensure timely, accurate data delivery. • Ensure high performance, privacy, security, scalability, and reliability in our solutions. • Work with and across Agile teams to design, develop, test, implement, and support technical solutions.

Requirements

• Bachelor’s Degree in Computer Science • Minimum of 2-5 years in a Data Engineering role, with at least 1 year of experience in cloud computing (AWS preferred) • Practical experience with data warehousing concepts, methodologies, and frameworks. • Expertise and hands-on experience in ETL development, deployment and monitoring • Profound knowledge of SQL, experience with OLAP databases (e.g., Redshift) and OLTP databases (e.g., MongoDB) • Proficiency in Python • Strong capability in data-driven problem-solving and critical analysis • Demonstrated ability to build and manage sophisticated data pipelines and storage solutions • Exceptional focus on meticulousness and accuracy in all aspects of work • Commitment to continuous professional development and embracing new technologies and methodologies • Experience in healthcare data management is highly desirable, but not mandatory.