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Data Engineering Manager
Divisions Maintenance Group
Facilities maintenance services across diverse industries, offering technical and building management solutions.
Build and manage revenue data pipelines & models to enable insights across the organization.
Partner with RevOps, Sales, and Finance leaders to translate business needs into data roadmaps and actionable insights that guide territory design, pricing strategies, and resource allocation.
Publish certified datasets and semantic layers to Power BI, enabling self_service dashboards for pipeline health, contracted margin, and funnel velocity.
Document data contracts, definitions, and best practices; coach analysts and stakeholders on leveraging curated datasets and reducing ad_hoc engineering requests.
Design and orchestrate efficient ELT pipelines in SQL and Python using tools such as dbt, Airflow and Glue to refresh critical tables in hours, not days.
Work with the data teams to Architect and maintain a Customer & Revenue 360° data model that unifies Snowflake, Salesforce, NetSuite, Dialpad, HRIS, and external enrichment data to be consumed by the entire organization.
Implement pragmatic data_quality, freshness, and lineage checks to ensure GTM metrics remain accurate and trusted.
What you bring
snowflake
postgres
fivetran
airflow
python
sql
Proven ability to translate business concepts into a clear data roadmap and technical execution plan.
Advanced experience with cloud data platforms - preferably Snowflake and Postgres - including ETL/ELT, data modeling, and performance tuning.
8+ years of full_time data_engineering experience delivering end_to_end solutions that support Sales, Marketing, or Finance.
Ability to manage the stress of a fast-paced environment.
Ability to meet the in-person requirements of the team and/or business needs.
Demonstrated success integrating Salesforce data and at least one ERP/billing system (NetSuite preferred); familiarity with CDC tools such as Fivetran or Airbyte is a plus.
Familiarity with AWS Glue, PySpark, Scala, Kafka, or similar technologies is advantageous.
Experience publishing enterprise_grade data models into the data warehouse including DAX Measures and workspace governance.
Solid understanding of data management best practices: ingesting new data, transforming/harmonizing it, and making it actionable for analytics.
Excellent communication and collaboration skills, with the ability to work across technical and non_technical teams in a fast_paced environment.
Expert_level SQL (minimum 5 years writing complex queries) and strong Python skills; hands_on experience with Airflow or Glue.
Benefits
Dollar-for-dollar 401K match up to 4% of salary with immediate 100% vesting.
Health, dental and vision coverage on day 1.
Paid time off to volunteer.
Employee Assistance Program to assist with everyday challenges.
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