Job Opportunities API

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