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Senior Data Engineer Backend (Vancouver)

Join Flagler Health as a Senior Data Engineer to develop and optimize data pipelines on the Databricks platform.

Location
Vancouver, Canada
Compensation
Not disclosed
Level
senior
Type
full time

Posted by employer 7 months ago

First seen on Joblaze 5 days ago

Last verified on the company career page 5 days ago

Apply at Flagler Health → Save job Scanned from flaglerhealth.io

Skills & Technologies

Requirements

Experience
5+ years

Not disclosed in this posting: compensation, work arrangement, visa sponsorship.

Joblaze summary

In this role, the Senior Data Engineer focuses on developing and optimizing data pipelines using the Databricks platform while ensuring the reliability of Spark applications. Proficiency in Python, particularly in object-oriented programming and API development, is essential, along with experience in managing MongoDB for efficient data handling. This position is well-suited for someone with a strong background in large-scale data processing and distributed systems, ideally at a senior level. Flagler Health is in a growth phase following a Series B funding round, emphasizing a collaborative and innovative team culture.

Joblaze insights

Quick facts

How much experience is required?
At least 5 years of relevant experience for this Senior Data Engineer Backend (Vancouver) role.
What's the tech stack?
Joblaze extracted these technologies from the posting: Databricks, MongoDB, Python, Spark.
What seniority level is this role?
Flagler Health targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Senior Data Engineer Backend (Vancouver) role at Flagler Health.

From the original posting

Flagler Health is building the clinical operating system for modern musculoskeletal care.

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.

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.

Our Values:

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

  • Owner: We own our work like founders. We don't wait to be asked, and we pick up the problem nobody else has.

  • Builder: We like making things from scratch. We don't need a playbook to start, and we'd rather ship a rough first version than wait on a perfect spec.

  • Fast: We make quick decisions. We favor progress and respect process.

  • Transparent: We communicate directly. We value merit and honesty, and we challenge assumptions, including our own.

  • Curious: We explore new approaches and ask "why" often.

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