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Senior Software Engineer, Data Platform

Role overview

Qualifications

  • Strong proficiency in SQL
  • Hands-on experience with dbt
  • Experience with batch orchestration tooling Dagster/Airflow
  • Proficiency in Python for data engineering tasks

Responsibilities

  • Build and extend batch pipelines using dbt and Dagster
  • Develop and optimize BigQuery data models
  • Advance real-time streaming capabilities with Kafka/PubSub and Flink
  • Improve reliability and observability of data pipelines

About the company

Apella logo

Apella

Digital Health & Health Tech

Apella is a technology company for better surgery. We use artificial intelligence, computer vision, and modern communications to improve the most critical aspect of healthcare.

Company details

Company typeStartup
IndustryDigital Health & Health Tech
Company size11 - 50

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Job description

Who we are:

Apella is applying computer vision and machine learning to improve the standard of care in the most critical aspect of healthcare: surgery. We build applications to enable surgeons, nurses, and hospital administrators to deliver the highest quality care.

Who you are:

We’re looking for a Senior Software Engineer, Data Platform to help evolve and operate our modern cloud data platform. You’ll build and maintain a BigQuery data warehouse with batch pipelines powered by dbt + Dagster, while also expanding a real-time streaming platform consisting of Kafka topics and Flink jobs (FlinkSQL) to process data as it arrives.

This role is ideal for someone who enjoys designing reliable data systems end-to-end: modeling and transforming data, orchestrating pipelines, enabling self-serve analytics, and ensuring the platform is observable, performant, and cost-effective.

In this role you'll:

  • Build and extend batch pipelines using dbt for transformations and Dagster for orchestration, scheduling, and asset-driven lineage.

  • Develop and optimize BigQuery data models (dimensional, wide-table, or domain-oriented) to support analytics, experimentation, and reporting use cases.

  • Advance real-time streaming capabilities by implementing and maintaining Kafka/PubSub + Flink pipelines, primarily using FlinkSQL, to deliver low-latency datasets and event-derived metrics.

  • Design data platform standards: SDLC, naming conventions, modeling patterns, incremental strategies, schema evolution approaches, and best practices for batch + streaming including CI/CD and testing.

  • Improve reliability and observability by implementing monitoring, alerting, and SLAs/SLOs for pipelines and data quality.

  • Partner with analytics, product, and engineering teams to onboard new data sources, define contracts, and deliver trusted datasets.

  • Own platform operations including performance tuning, data quality, cost optimization, and scaling across both warehouse and streaming systems.

  • Design a unified serving layer architecture that cleanly exposes consistent, trusted datasets across both batch and streaming systems.

  • Establishing strong data governance, reliability standards, and observability practices.

What you'll bring:

  • Strong proficiency in SQL (advanced querying, performance considerations, data modeling).

  • Hands-on experience with dbt (models, tests, sources, macros, snapshots, incremental strategies).

  • Experience with batch orchestration tooling Dagster/Airflow (assets/jobs, schedules/sensors, partitioning, backfills, observability).

  • Proficiency in Python for data engineering tasks (pipeline glue code, libraries, tooling, testing).

  • Deep familiarity with BigQuery or equivalent cloud native data warehouse tooling (partitioning/clustering, cost/performance optimization, best practices).

  • Solid experience with GCP (AWS/Azure) infrastructure (core services, IAM, security practices, deployments/automation).

  • Strong engineering fundamentals: version control, testing, code review, documentation, and operational ownership.

Nice to have

  • Experience with data quality tooling and patterns (e.g., anomaly detection, expectation-based testing, lineage).

  • Experience designing semantic layers or metrics layers for analytics.

  • Familiarity with event-driven architectures, schema registries, CDC patterns, and schema evolution strategies.

  • Experience building or maintaining streaming data pipelines with Kafka and Apache Flink, including FlinkSQL.

  • Experience with IaC (e.g., Terraform) and CI/CD for data platforms.

  • Understanding of privacy/security controls (PII handling, access controls, auditability).

What to expect from our interview process:

  • Chat with Our Recruiter – A quick intro to get to know you and share more about Apella & the role

  • Complete a Coding Exercise – Work through a collaborative coding exercise with one of our engineers

  • Virtual Onsite Interviews – Meet a few team members and dive into areas like collaboration, culture, and role-specific skills. Typically 3-4 interviews

  • Meet with one or two of our founders – Usually "reverse interview" style where you can ask questions and make sure we're the right fit for you

Our benefits:

  • Competitive salary and stock options

  • Flexible vacation policy and a culture that values time for rest and recharging

  • Remote-first work environment with unique virtual and in-person events to foster team connection

  • Comprehensive health, dental, and vision insurance—we're a healthcare company that prioritizes your health

  • 16 weeks of parental leave for all parents

Apella is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We encourage people from all backgrounds to apply to our roles.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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