Data Engineering Architect (Databricks)

TL;DR

Data Engineering Architect (Databricks): Designing and operating scalable data pipelines and a Lakehouse architecture to deliver high-quality datasets for analytics and AI with an accent on data modeling, governance, and performance tuning. Focus on building production-grade Gold layer datasets, optimizing SQL at scale, and establishing reusable engineering patterns.

Location: Onsite in Arlington, US

Company

hirify.global is a leading source of legal, tax, regulatory, government, and business information for professionals.

What you will do

• Translate business KPIs and data requirements into scalable, production-grade datasets.
• Own the design, build, and operation of end-to-end data pipelines (ingestion → transformation → serving).
• Evolve the Databricks-based Lakehouse architecture to improve structure, scalability, and consistency.
• Build and maintain governed Gold layer datasets to power analytics and AI/ML use cases.
• Develop and enforce reusable data engineering patterns and standards to reduce duplication.
• Ensure data quality and reliability through validation, monitoring, SLAs, and incident resolution.

Requirements

• 8+ years of experience in data engineering with a track record of owning production data systems.
• Deep expertise in SQL, including query optimization and performance tuning at scale.
• Hands-on experience with Python and distributed frameworks like Databricks or Spark.
• Strong understanding of Lakehouse architecture, ELT, and layered data models (bronze/silver/gold).
• Experience developing source-controlled pipelines in a CI/CD environment.
• Bachelor’s degree in Computer Science or a related discipline.

Nice to have

• Experience working with product analytics data (event tracking, user behavior, experimentation).
• Master’s degree in Computer Science or a related field.

Culture & Benefits

• Collaborative environment partnering closely with product, analytics, and engineering teams.
• Opportunity to work with a modern cloud stack including Databricks, AWS, and GCP.
• Commitment to equal opportunity and a non-discriminatory professional workplace.