Senior Data Engineer Backend (Vancouver)

We partner with MSK provider groups and specialty clinics to help them grow, operate more efficiently, and deliver better longitudinal care across patient acquisition, clinical workflows, and ongoing patient engagement. Our platform sits at the intersection of care delivery and clinic operations, helping providers capture more value across the full patient lifecycle.

We’ve recently raised our Series B and are entering our next phase of growth. We’re hiring a Head of Marketing to build and scale the marketing engine that will drive that growth.

This is a pipeline and revenue role. Success means generating high-quality pipeline from the right provider groups, and helping convert that into revenue in a complex, trust-driven market.

Key Responsibilities

Databricks Platform Expertise
• Develop, manage, and optimize data pipelines on the Databricks platform.
• Debug and troubleshoot Spark applications to ensure reliability and performance.
• Implement best practices for Spark compute and optimize workloads.
• Python Development:
• Write clean, efficient, and reusable Python code using object-oriented programming principles.
• Design and build APIs to support data integration and application needs.
• Develop scripts and tools to automate data processing and workflows.

MongoDB Management
• Integrate, query, and manage data within MongoDB.
• Ensure efficient storage and retrieval processes tailored to application requirements.
• Optimize MongoDB performance for large-scale data handling.
• Collaboration and Problem Solving:
• Work closely with data scientists, analysts, and other stakeholders to understand data needs and deliver solutions.
• Proactively identify and address technical challenges related to data processing and system design.

Required Qualifications
• Proven experience working with Databricks and Spark compute.
• Proficient in Python, including object-oriented programming and API development.
• Familiarity with NoSQL (MongoDB preferred), including querying, data modeling, and optimization.
• Strong problem-solving skills and ability to debug and optimize data processing tasks.
• Experience with large-scale data processing and distributed systems.

Preferred Qualifications
• Strong understanding of data architecture, ETL processes, and data warehousing concepts.
• Knowledge of other big data technologies like Delta Lake, Hadoop, or Kafka.
• Experience with cloud platforms (e.g., AWS, Azure, or GCP).
• Familiarity with CI/CD pipelines and version control systems like Git.

This is what you can expect of your teammates at Flagler:

• Persistence + ownership of outcomes: We wear many hats and aren’t afraid to run through walls to solve hard problems.

• Personal + professional growth: We push ourselves to learn new things and embrace challenges, even if it means that we sometimes fail.

• Don’t take things personally: We value and react quickly to constructive feedback.

• Speed is our ally: In the fast-paced world of startups, we understand the value of moving swiftly. We thrive on the adrenaline of working rapidly.

• Be Right: We are highly detailed oriented and try to be right, a lot.