Senior Data Engineer

About Us: ZenaTech (Nasdaq: ZENA | FSE: 49Q) is a technology company specializing in AI drones, Drone-as-a-Service (DaaS), enterprise SaaS, and quantum computing solutions for mission-critical business applications. Since 2017, the company has leveraged its software development expertise and expanded its drone design and manufacturing capabilities through ZenaDrone to innovate and enhance customer inspection, monitoring, safety, security, compliance, and surveying processes. ZenaTech serves over 100 enterprise software customers in law enforcement, government, and industrial sectors, with drones used in agriculture, defense, and logistics industries. The company has offices in North America, Europe, and the UAE. This position will be at our 250 University Ave, Toronto, ON M5G location. Overview: The Senior Data Engineer, Operations will build and own the consolidated operational data model that everything else depends on. Every acquired firm arrives with its own accounting, scheduling, and job management systems. This role turns that into a single queryable source of truth so analysts analyse rather than reconcile. Responsibilities Design, build, and maintain the operational data warehouse and ingestion pipelines Integrate source systems across acquired entities in both regions, including systems that will never be migrated off Map inconsistent charts of accounts, job codes, and service line taxonomies to a common model Own data quality: validation, reconciliation to the general ledger, monitoring and alerting Build and maintain the semantic layer the analysts and BI tools sit on Scope data migration effort during acquisition diligence Set technical standards and mentor the second engineer Requirements 5+ years in data engineering, with demonstrated experience integrating fragmented or legacy source systems Strong SQL and Python; hands-on with a modern warehouse (Snowflake, BigQuery, Redshift, or Databricks) and a transformation framework such as dbt Experience ingesting from small-business accounting platforms — QuickBooks, Sage, NetSuite — which is what most acquired firms run Pragmatic about scope: delivers a usable dataset in weeks rather than architecting for three quarters Comfortable working directly with non-technical branch staff to establish what a field actually means Artificial Intelligence We use artificial intelligence to review and screen applications and materials. However, every candidate we move forward with is reviewed and selected, and all final hiring decisions are made by a member of our hiring team. “We are an equal opportunity employer committed to employment equity utilizing hiring practices on merit and business needs. We encourage applications from women, Indigenous peoples, persons with disabilities, members of visible minorities and all others of legally protected status.”

The role involves designing and maintaining an operational data warehouse and ingestion pipelines to consolidate data from various acquired entities. The engineer will map inconsistent financial and operational taxonomies into a single queryable source of truth for analysts.

Candidates need over 5 years of data engineering experience with strong proficiency in SQL, Python, and modern cloud warehouses. Experience integrating small-business accounting platforms like QuickBooks or Sage is specifically required.

• SQLSouhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Data Engineering
• SQL
• Python
• Snowflake
• BigQuery
• Redshift
• Databricks
• dbt
• Data Warehousing
• ETL Pipelines
• Data Modeling
• Data Quality
• Semantic Layer
• Data Migration
• QuickBooks
• NetSuite

• Data & Analytics
• Engineering
• Technology
• Software
• Finance & Accounting

Expérience minimale

5+ ans

Postuler avant le

20 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Mid-Senior level

Mode de candidature

La candidature directe est offerte