Principal Consultant, Data Engineer (Level 4) (Databricks)

TL;DR

Principal Consultant, Data Engineer (Databricks): Deliver strategic client engagements in data warehousing, ETL/ELT development, data integrations, and modeling with an accent on Databricks, AWS, and Azure technologies. Focus on leading end-to-end pipeline implementations, mentoring juniors, and ensuring scalable, secure data solutions.

Remote in the US and Canada (Ontario) with preference for HQ locations: DC Metro, Chicago Metro, Toronto Metro. Not eligible for candidates requiring sponsorship to work in the US.

Company

hirify.global is a Databricks-focused data and AI consulting firm serving high-profile enterprise clients across Media & Entertainment, Manufacturing, Retail & CPG, Healthcare & Life Sciences, and Financial Services.

What you will do

• Lead client-facing projects independently, managing execution, status updates, and roadblocks with stakeholders.
• Collaborate with teams to deliver data engineering projects, including ETL/ELT pipelines and data warehousing with performance enhancements.
• Own project planning, solution design, real-time data processing, streaming, security, and compliance for pipelines.
• Implement version control, branching strategies, and CI/CD integration.
• Mentor junior data engineers and develop people management skills.

Requirements

• B.S. in Computer Science or equivalent.
• 4+ years in data engineering and big data; at least 2 years in professional services with direct client interaction.
• Extensive Databricks experience for deploying pipelines (must-have).
• Data modeling, database design, and version control skills.
• Experience architecting scalable data solutions on Azure, AWS, and Databricks.
• Excellent verbal and written communication skills.

Nice to have

• Databricks Data Engineer Professional certification.
• Preference for candidates with Databricks Professional certifications.

Culture & Benefits

• Exciting projects with Fortune 100 to small businesses across global verticals.
• Work closely with experienced data engineers to grow skills rapidly.
• Collaborative, dynamic, inclusive environment encouraging innovation and challenging the status quo.
• Diverse team of data experts, experience seekers, and entrepreneurial minds.