Lovelytics

www.Lovelytics.com

1 Job

582 Employees

About the Company

Lovelytics is a leading data, AI, and analytics consulting firm headquartered in Arlington, Virginia, with team members across the US, Canada, Argentina, Colombia, and Spain. Backed by Databricks Ventures and Interlock Equity, Lovelytics specializes in delivering cutting-edge solutions within the Databricks ecosystem, earning consistent recognition as a top Databricks partner. Lovelytics also partners with Microsoft Azure, Google Cloud, and AWS to bring Databricks to clients across all major cloud platforms.

Listed Jobs

Company Name: Lovelytics
Job Title: Principal Consultant, Data Engineer (Level 4)
Job Description: **Job Title** Principal Consultant, Data Engineer (Level 4) **Role Summary** Senior client‑facing data engineering consultant responsible for designing, deploying, and optimizing data pipelines and warehouses on Databricks, AWS, and Azure. Leads small to medium‑scale projects, mentors junior engineers, and collaborates with stakeholders to deliver high‑quality, scalable data solutions. **Expectations** - Own end‑to‑end delivery of client engagements, including project planning, execution, and status reporting. - Demonstrate leadership in data engineering, securing budget approval and maintaining client satisfaction. - Mentor and coach junior team members to elevate team capability. - Drive continuous improvement of processes, security, and performance. **Key Responsibilities** - Design, implement, and maintain ETL/ELT pipelines on Databricks. - Develop data warehouses, lakehouse schemas, and real‑time streaming solutions. - Apply security and compliance controls to all data assets. - Manage version control, branching strategies, and CI/CD pipelines. - Collaborate with clients and internal stakeholders to refine requirements and deliver solutions on schedule. - Mentor junior engineers and promote professional growth. - Serve as engagement lead on small projects or as a supporting lead under senior guidance. **Required Skills** - 4–6 years of data engineering experience, 2 years in professional services with client interaction. - Deep expertise in Databricks (including Advanced Analytics features). - Proven experience with Azure and AWS data services. - Strong data modeling and database design capabilities. - Version control (Git) and CI/CD best practices. - Excellent written and verbal communication. - Ability to architect fault‑tolerant, scalable data solutions. **Required Education & Certifications** - B.S. in Computer Science or equivalent. - Databricks Data Engineer Professional certification strongly preferred. - Databricks Professional certifications (additional levels) a plus.