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Jobs(29,761)/Data Engineer Role(400)/Climb (1) - Senior Data Engineer
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Climb

Climb - Senior Data Engineer

United States5d ago
In OfficeSeniorNAFintechCloud ComputingData EngineerSenior Data EngineerApache SparkSQLAWSAzureGCPAirflowdbtData QualityGovernanceDatabricks

Requirements

• 6+ years in data engineering or analytics engineering. • Advanced experience building production data pipelines with Apache Spark (PySpark and SQL), including performance optimization. • Hands-on production experience with Databricks (Delta Lake, Jobs, Workflows, Unity Catalog). • Deep experience with at least one major cloud (AWS, Azure, or GCP). • Strong SQL and data modeling fundamentals. • A track record of building and operating production-grade data pipelines, not just prototypes. • Comfortable working directly with client stakeholders to translate business requirements into technical solutions. • Demonstrated ability to independently own a data engineering workstream from design through production. • Experience with Delta Live Tables, structured streaming, or real-time pipelines. • Familiarity with dbt, Airflow, or other modern data stack tooling. • A demonstrated performance- and cost-optimization mindset (cluster sizing, Photon, file layout, partitioning). • Exposure to governed or regulated environments (e.g., financial services, healthcare). • Prior consulting, systems integrator, or professional services experience. • Note on certification: Existing Databricks certifications are a plus. Where not already held, Databricks certification (e.g., Data Engineer Associate/Professional) is expected to be obtained post-hire. • This role is designed for engineers who are ready to own complete workstreams today and are growing toward whole-system architecture and engagement leadership. • You naturally take ownership of complete workstreams rather than waiting for individual tasks. • You treat data quality, reliability, and performance as product features, not afterthoughts. • You enjoy solving ambiguous problems with practical engineering. • You leave every platform easier to operate than when you found it. • You'd rather ship something maintainable than demo something clever.

Responsibilities

• Own one or more data engineering workstreams, from technical design through production deployment and handoff. • Design and implement scalable data models and lakehouse architectures, including medallion patterns where appropriate. • Optimize performance and cost across Databricks and the underlying cloud: you treat compute spend as your problem, not someone else's. • Orchestrate workflows using Databricks Workflows, Delta Live Tables, or equivalent tooling. • Implement governance, security, observability, and lineage with Unity Catalog, and stand up CI/CD for data. • Design and build AI-ready data platforms that enable reliable analytics, machine learning, and agentic applications. • Work directly with client stakeholders to gather requirements and translate them into technical solutions. • Review code, mentor junior engineers, and maintain high engineering standards across your workstreams. • Contribute reusable accelerators, frameworks, and best practices back to the practice.

Benefits

• Ground floor, real backing. You are joining early, with founders who have built and exited firms like this before. You help write the playbook rather than inherit one. • Ground floor, real backing. • Outcomes, not hours. We sell and deliver against business results. Advancement is tied to delivery performance and account impact, not utilization targets. • Outcomes, not hours. • Senior team, no body-shop drag. Small pods of A-players, heavy internal AI leverage, and no bloated middle layers between you and the work. • Senior team, no body-shop drag. • IP that compounds. Every engagement feeds reusable accelerators, patterns, and points of view back into the practice. • IP that compounds. • Competitive base salary with performance-based bonuses • MacBook Pro and swag kit so you can do your best work • Comprehensive health, dental, and vision insurance • Generous holidays, flexible PTO, and remote-first work environment • Professional development budget including Databricks and cloud certifications • Spot bonuses for relevant certifications • Conference attendance and thought leadership opportunities • Collaborative, low-ego culture with direct access to leadership • Opportunity to shape a growing practice from the ground floor

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