Data Engineer

Odaia Intelligence Inc.•Toronto, ON

19d•Remote

About The Position

ODAIA is a remote-first organization that works with pharma commercial teams to grow their brands and engage with 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, predict prescribing behaviors, and make informed decisions that bring therapies to patients faster. ODAIAns are inspired to reinvent the future of how non-technical people leverage data in their day-to-day lives. They are passionate about solving complex problems in data, AI, engineering, design, and product. The company values the notion that “simplicity is the ultimate sophistication;” and making simplicity scalable is an even bigger challenge. The team is led by serial entrepreneurs, tech veterans, and life sciences experts. ODAIA's mission is reducing patients’ time to therapy by facilitating meaningful interactions with healthcare providers, through human-centric software powered by AI. They are also on a mission to build an innovative, diverse, and ego-free business, where trust, innovation, and ownership are valued. Emphasis is placed on career development for employees, with extensive opportunities to grow.

Requirements

3+ years in data engineering, building production grade data pipelines
Strong experience with AWS (ECS, S3, Lambda, DynamoDB, 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, prioritize effectively, and adapt quickly to changing business needs
Excellent communication skills, capable of translating complex technical concepts for both technical and non-technical stakeholders

Responsibilities

Build scalable data infrastructure to support customer onboarding and implementation, enabling fast and efficient ingestion of customer data into ODAIA’s platform
Design and ship Claude-powered tools that reduce mean time to resolution (MTTR) for production incidents by automating error triage and fix proposals
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