About the role

Manager, RevOps Data Engineering managing revenue operations data engineering. Leading a global team for data management at Simpro Group.

Responsibilities

Lead and develop a team of data engineers and visualization specialists who ensure that the data flows smoothly from operational systems to data warehouses and are accessible for analysis, often using tools like SQL, Python, APIs and big data technologies.
Ensure the team provision trusted data for end users to analyze and report against by building user friendly data visualizations that are deployed across Simpro Group.
Own the certification of all, and the creation of the most important, operational dashes for revenue generating teams.
Design and implement complex data pipelines using Fivetran for optimal extraction, transformation, and loading of data from various sources.
Manage and optimize data queries and performance in Google BigQuery to ensure efficient data storage and retrieval.
Develop, monitor, and maintain a scalable data architecture, as well as optimize and oversee database performance.
Collaborate with cross-functional teams to translate business requirements into non-technical terms and data frameworks.
Ensure data integrity, compliance with data governance and security policies, and continuous availability of data for operational and analytical purposes.
Continuously evaluate new technologies and tools to enhance the data architecture and analytics capabilities of the organization.

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field; Master’s degree preferred.
Confidence in project management to successfully estimate, track, and complete milestones and deliverables for complex projects impacting many teams.
Demonstrated ability to prioritize highest impact initiatives under tight deadlines.
Strong EQ, enabling you to successfully engage at all levels of the organization and distill complex data systems into terms the business can ingest.
Proficiency in SQL is a must.
Knowledge and experience in Python is a plus.
Strong experience with ETL tools and methodologies.
In-depth knowledge of cloud-based data warehouses, particularly Google BigQuery.
Certifications in Google Cloud Platform are a plus.
Experience with data modeling, warehousing, and building ETL pipelines.
Knowledge of CI/CD for deployment of data pipelines (e.g. Github) a plus.
Prior exposure to machine learning algorithms and underlying data structures.
Demonstrated ability to work with large, heterogeneous datasets in building and optimizing data pipelines, architecture, and data sets.
Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
Excellent problem-solving skills and ability to translate business requirements into non-technical terms.

Responsible Time Off
Comprehensive medical, dental, vision package with 100% employer paid options
401k/Retirement Plan with 6% employer match
Generous Parental Leave Program
Paid Volunteer Leave Days
Public Holiday Exchange Scheme
Enjoy up to 4 weeks a year of flexible 'Work from Anywhere' time!
Talent Referral Program – get rewarded for referring a friend to join our team!
Diverse training & internal networking opportunities across all of our product lines
Opportunities for career progression and development