Data Engineer

ABOUT ODAIA

ODAIA noun: o
· da·ia | 'oh-day-yeah, an Ancient Greek word referring to “tools of the trade.” To learn more visit odaia.ai.

ODAIA is a remote first organization; all our positions are WFH with frequent company and team based socials, events and meetings in-person and virtually.

ODAIA works with pharma commercial teams to grow their brands and engage with the right healthcare professionals (HCPs) at the right time. ODAIA's SaaS AI platform turns complex data into personalized insights, enabling commercial teams to understand their customers – (HCPs), predict prescribing behaviors and make informed decisions that bring therapies to patients faster.

ODAIAns (what we call ourselves) are inspired to reinvent the future of how non-technical people leverage data in their day-to-day lives. We are passionate about solving complex problems in data, AI, engineering, design, and product, so our customers don’t have to. We live by the notion that “simplicity is the ultimate sophistication”; and making simplicity scalable is an even bigger challenge.

That’s why we have a crazy talented team led by serial entrepreneurs, tech veterans, and life sciences experts.

To learn more visit odaia.ai.

Reducing patients’ time to therapy by facilitating meaningful interactions with healthcare providers, through human-centric software powered by AI.

We’re also on a mission to build an innovative, diverse, and ego‑free business, where trust, innovation and ownership are valued. You’re on a mission too? We’re here for it. We put an emphasis on career development for our employees, and the opportunities to grow are extensive.

Reporting to the Director, Data Management and as a member of the Data Management team, the Data Engineer i is passionate, curious and motivated to design and implement scalable solutions end-to-end. This high‑impact position focuses on key aspects of data management including fast and efficient data onboarding, and the initial bring up of customer data into our system.

• Build scalable data infrastructure to support customer onboarding and implementation, enabling fast and efficient ingestion of customer data into ODAIA’s platform
• Design and develop automation tools that streamline how implementation consultants configure and ingest new customer datasets
• Solve complex data challenges by defining, prototyping, and implementing end-to-end data solutions in agile startup environment
• Serve as a subject matter expert to internal teams and customers on data integration, architecture, and management best practices
• Implement scalable ingestion pipelines leveraging AWS tools and services to manage high‑volume customer data
• Develop integrations with Veeva/Salesforce and other third‑party data sources; contribute to proof‑of‑concept builds and internal applications
• Design APIs and data models that enable internal data access and cross‑system interoperability
• Explore and onboard new data sources, designing warehouse schemas that improve analytics and product capabilities
• Collaborate cross‑functionally with product and engineering teams to align data systems with strategic objectives

• 3+ years in data engineering, building production grade data pipelines
• Strong experience with AWS (ECS, S3, Lambda, Dynamo
  
  DB, API Gateway, etc.) and Snowflake
• Experience with Dagster or Airflow for orchestration and workflow management
• Strong programming proficiency in Python
• Experience building and optimizing complex data models utilizing DBT with a strong understanding of ETL processes
• Solid understanding of data structures, algorithms, and database design, with expertise in performant SQL schema and query development
• Familiarity with CI/CD and Test Driven Development in a production environment
• Experience integrating with CRM systems (Veeva, Salesforce) and handling healthcare, pharmaceutical, or pharmacy‑related datasets is a strong asset
• Solid, demonstrated experience in AWS stack or an equivalent cloud platform
• Background in modernizing data environments, migrating from legacy systems to cloud‑native architectures
• Collaborative and self‑directed, able to manage projects independently,…