Principle Data Engineer

Principal Data Engineer

Location: Boca Raton, FL (Hybrid / Remote Flexible)

Position Type: Full-Time, Permanent

The Opportunity & Impact

Burtch Works has partnered with a growing software engineering firm that builds a proprietary, AI-driven data engine for the home services sector. The platform predicts consumer service needs across the industry—spanning residential maintenance, specialty trades, and property improvements—allowing businesses to target customers with precision.

The organization is on a steady growth trajectory and needs a visionary builder rather than a traditional pipeline maintainer. This position offers total technical ownership over an ecosystem that ingests, models, and processes billions of data points—including massive geospatial datasets, real-time meteorological tracking, and complex third-party consumer demographics. The core mission is to lead the modernization of legacy warehouse infrastructure into a world-class, cost-efficient, and highly scalable Azure Data Lakehouse that fuels predictive AI products.

Key Responsibilities

• Architect for Scale: Lead the technical modernization of a legacy data warehouse into a high-performance Azure Data Lakehouse architecture built to handle continuous, exponential growth.
• Own the Core Data Engine: Design, build, and optimize robust ingest frameworks for complex, disparate data flows—blending high-volume municipal feeds, real-time weather analytics, and high-velocity lead generation data.
• Bridge Engineering & Data Science: Partner closely with the Data Science team to construct durable, leakage-resistant feature pipelines and MLOps workflows that accelerate model deployment.
• Enforce Data Reliability: Design and implement automated data validation, quality monitoring, and schema contracts to ensure zero downstream failure for production AI models.
• Optimize for Efficiency: Drive cost-awareness and high performance across Azure environments through expert query tuning, smart partitioning, and distributed compute frameworks.
• Champion the Tech Stack: Act as the hands-on technical lead within a nimble, fast-moving team, championing modern development practices, mentoring engineers, and maintaining clean, testable, production-ready Python and SQL codebases.
  
  

Qualifications & Experience

• Deep Architectural Expertise: 8 years of experience in data platform development, with a proven track record of designing data lakehouses and production pipelines at scale within complex, multi-source data environments.
• Master of the Azure Ecosystem: Extensive, hands-on experience building within Azure infrastructure, specifically utilizing Azure Data Lake, Azure Data Factory, Azure Synapse, and/or Databricks.
• Core Technical Excellence: Expert-level Python (OOP, data profiling, testing frameworks) and advanced SQL (complex analytical queries, recursive CTEs, and deep performance optimization).
• AI/ML Infrastructure Familiarity: Direct experience supporting the MLOps lifecycle—packaging models via Docker, handling automated model registries, and setting up reproducible feature stores is highly preferred.
• The "Builder" Mindset: A proactive, reliability-first approach to software engineering, with the ability to move fast in an agile environment, diagnose complex data bottlenecks, and explain architectural trade-offs in clear business terms.
• Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related quantitative field—or equivalent deep, hands-on industry experience.
  
  

Why Join?

• Direct Impact: Total technical ownership over the foundational data asset powering an entire product suite during a pivotal expansion phase.
• Innovative Culture: Opportunity to work in a collaborative, tech-heavy environment alongside software designers, UX specialists, and data scientists utilizing cutting-edge LLMs and automation.
• Flexibility & Balance: A flexible remote culture with a dedicated home office stipend, department meetups, and a highly collaborative team dynamic.