Remote, Alaska 99501 Posted February 26th, 2026
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Job Type: Full Time
Job Category: IT
Job Description
Role : Senior Databricks Developer Location: Remote Full Time
Job Description
Must Have Technical/Functional Skills
- 7+ years of experience in Data Engineering, with 3–5+ years on Databricks. - Advanced proficiency in Apache Spark, PySpark, SQL, and distributed data processing. - Strong experience with DBT (Core or Cloud) for building robust transformation layers. - Hands-on expertise in data asset modeling, curation, optimization, and lifecycle management. - Proven experience with job tuning, performance debugging, and cluster optimization. - Experience implementing observability solutions for data pipelines. - Solid understanding of Delta Lake, lakehouse architecture, and data governance. - Experience with cloud platforms (Azure preferred; AWS/GCP acceptable). - Strong Git-based development workflows and CI/CD experience.
Roles & Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and Spark SQL. - Optimize Spark jobs—including partitioning, caching, cluster sizing, shuffle minimization, and cost-efficient workload design. - Build and manage workflows using Databricks Jobs, Repos, Delta Live Tables, and Unity Catalog. - Develop and refine DBT models, tests, seeds, macros, and documentation to support standardized transformation layers. - Implement modular, version-controlled DBT pipelines aligned with data governance and quality practices. - Partner with data consumers to ensure models align with business definitions, lineage, and auditability. - Create curated, reusable, and well-governed data assets (gold/silver/bronze layers) for analytics, reporting, and ML use cases. - Continuously refine and optimize data assets for consistency, reliability, and usability across teams. - Drive standardization of data patterns, frameworks, and reusable components. - Identify and implement engineering efficiencies across Databricks and Spark workloads—cluster optimization, code improvements, auto-scaling patterns, and job orchestration enhancements. - Collaborate with platform engineering to enhance DevOps automation, CI/CD pipelines, and environment management. - Improve cost governance through workload analysis, optimization, and proactive cost monitoring. - Conduct Spark job tuning and pipeline performance optimization to improve processing speed and reduce compute spend. - Troubleshoot production issues and deliver durable fixes that improve long term reliability. - Implement best practices for Delta Lake performance (ZORDER, auto-optimize, vacuum, retention tuning). - Implement end-to-end observability for data pipelines, including logging, metrics, tracing, and alerting. - Integrate Databricks with monitoring ecosystems (e.g., Azure Monitor, CloudWatch, Datadog). - Ensure pipeline SLAs/SLOs are clearly defined and consistently met. - Work closely with data architects, analysts, business SMEs, and platform teams. - Provide technical leadership, review code, mentor junior engineers, and advocate for engineering excellence. - Translate business requirements into scalable, production-quality data solutions.
Required Skills
CLOUD DEVELOPER
SQL APPLICATION DEVELOPER