Role Overview In this role, you will manage a team of Data Engineers and work in close collaboration with Development team, Data Analysts from our Assets, Pro Services, Support, and Migration teams. You’ll lead architecture, integration strategy, and enforcement of data standards, while ensuring that our data infrastructure enables fast, accurate, and secure delivery of data assets across the business.

Key Responsibilities Team & Technical Leadership · Manage, mentor, and grow a team of Data Engineers, fostering a high-performance, collaborative culture. · Work closely with Data Analysts across Assets, Pro Services, Support, and Migration teams to ensure that the underlying data infrastructure supports their needs. · Oversee project planning, technical decision-making, and timely delivery of engineering initiatives. Data Engineering & Platform Ownership · Architect, build, and optimize data pipelines for ingestion from SaaS tools (e.g., PSA, RMM, monitoring platforms). · Own and scale our data infrastructure on cloud platforms (AWS, GCP, Azure). · Implement and maintain CI/CD processes for data workflows and transformations. Data Integration & Standardization · Design unified data models across disparate MSP tools; lead cross-system integration and data normalization. · Partner with Development and DA teams to ensure data consistency and traceability across outputs. · Manage syncing frequency and storage policies in line with platform performance. Data Governance & Compliance · Develop and enforce governance frameworks for data quality, metadata management, access control, and classification. · Define and monitor Data Quality Indicators (DQIs) for accuracy, completeness, and timeliness. · Establish data access policies, audit trails, and compliance processes (e.g., GDPR, SOC 2), and participate in audits and risk assessments. Data Cataloging & Metadata Management · Maintain clear documentation of data sources, data lineage, and business logic via data catalogs and dictionaries. · Promote standardized definitions, usage policies, and master data consistency across all client assets. Stakeholder & Client Collaboration · Collaborate with internal teams—including Data Analysts from all business units—to translate requirements into scalable, reliable data solutions. · Support dataset, widget, and dashboard development by providing governed, high-quality data structures. Promoting a Data-Driven Culture · Drive adoption of reusable, governed data assets by product, customer success, and operations teams. · Lead internal training sessions and promote best practices in data governance, usage, and security.

Required Qualifications · Education: Bachelor’s or Master’s in Computer Science, Information Management, or related fields. · Experience: 5+ years in data engineering, with at least 2 years managing data teams. · Proven experience with data governance frameworks (e.g., DAMA DMBOK) and metadata management. · Strong hands-on skills in PostgreSQL (including performance tuning), SQL, and Python. · Solid understanding of data warehouse/lake architecture, ETL/ELT processes, and data modeling. · Familiarity with tools like Airflow, dbt, Informatica, or similar. · Experience integrating with MSP ecosystem platforms (e.g., ConnectWise, Kaseya, Datto, N-able). · Knowledge of compliance frameworks including GDPR, CCPA, SOC 2.

Preferred Qualifications · Fluent in English, with ability to lead or participate in English-speaking client and team meetings. · Familiar with data visualization platforms (e.g., Power BI, Tableau). · Familiar with DevOps and IaC tools (Terraform, CloudFormation). · Experience managing large-scale migrations or client onboarding from platforms like BrightGauge.

Soft Skills & Abilities · Strong project management and prioritization capabilities across multiple stakeholders. · Excellent written and verbal communication skills across technical and non-technical teams. · Organized, adaptable, and able to thrive in a dynamic, fast-paced environment.