Who you are

• In addition to the technical capabilities for this role, we are looking for someone who wants to work in a collaborative, dynamic, and inclusive environment and has a passion for bringing meaning to data
• B.S. in Computer Science or equivalent
• 4-6 years' experience in data engineering and big data. At least 2 years' of professional services experience interacting directly with clients
• Extensive knowledge of data warehousing concepts and hands-on experience deploying pipelines using Databricks **a must
• Databricks Data Engineer Professional certification a plus
• Data modeling and database design skills and knowledge of version control
• Excellent verbal and written communication skills
• Experience architecting scalable and fault-tolerant data solutions across Azure, AWS, and Databricks
• Understands and utilizes Lovelytics tools and client tools
• Preference for candidates with Databricks Professional certifications

What the job involves

• Lovelytics is seeking a Data Engineering Principal Consultant with extensive Databricks experience to join our team and help deliver strategic client engagements
• As a Principal, you will gain people management skills to develop to the next level
• In addition, you will play a key role, often as an engagement lead, on client engagements related to data warehousing, ETL development, data integrations, and data modeling
• This is a client-facing and stakeholder management role, focused on using and migrating to our partner technologies; Databricks, AWS, and Azure to name a few
• Utilize consulting and technical skills to be able to work in a client-facing project environment independently
• Be responsible for your own execution and often others' on client projects, communicating directly with internal and external stakeholders on status updates and potential roadblocks
• Collaborate with other team members to successfully deliver on projects
• Work effectively and directly communicate with both internal and client and/or partner teams
• Develop full ownership of your execution on client engagements, play a role in the project planning and solution stages of engagements as well
• Successfully lead small Data Engineering projects and workstreams with measurable performance enhancements typically under the management of an engagement lead, or may play the part of the EL
• Lead the end-to-end implementation of multiple ETL/ELT pipelines, demonstrating efficient data transformation
• Mentor junior data engineers, and their growth is evident in their project contributions
• Successfully lead small data warehousing projects with measurable performance enhancements under the management of an engagement lead- may also play the role of an engagement lead
• Contribute to real-time data processing solutions and managed streaming data
• Implement security and compliance measures for data pipelines
• Design and implement version control and branching strategies and integrate them into CI/CD for promoting and testing in higher environments