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Tucows Inc.

Analytics Engineer (dbt)

Canada; CanadaRemote · Canada
Analytics & Insights
POSTED 6 OCTVERIFIED 1D AGO
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Role
34 days opentrue age
Posted 6 Oct
Pay
CAD 109k–CAD 133kno pay posted
Market p25–p75
CAD 109k–CAD 133k
Canada · n=10 · 365d to 6 Nov
CompanyTucows Inc. →
10open roles
Opened · 30d
+0
Closed · 30d
−0
30d window
Market
1,635open · Data engineering
Opened · 7d
+1117% of open
All data engineering
3,809open
All tracked boards · live 9 Nov · n=1,635
PythonAirflowSnowflakedbtSQL

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd!

About the opportunity

We are seeking an experienced and versatile Analytics Engineer to join our dynamic team. In this role, you will apply your advanced analytics expertise to extract actionable insights from raw data. The ideal candidate will have a strong background in data engineering, analytics, and machine learning, with the ability to drive data-driven decision-making across the organization.

What You Will Be Doing

  • Data Modeling & Pipelines: Design, develop, and maintain complex data models in our Snowflake data warehouse. Utilize dbt (Data Build Tool) to create efficient data pipelines and transformations for our data platform.
  • Snowflake Intelligence Integration: Leverage Snowflake Intelligence features (e.g., Cortex Analyst, Cortex Agents, Cortex Search, AISQL) to implement conversational data queries and AI-driven insights directly within our data environment. Develop AI solutions that harness these capabilities to extract valuable business insights.
  • Advanced SQL & Analysis: Design and build advanced SQL queries to retrieve and manipulate complex data sets. Dive deep into large datasets to uncover patterns, trends, and opportunities that inform strategic decision-making.
  • Business Intelligence (BI): Develop, maintain, and optimize Looker dashboards and LookML to effectively communicate data insights. Leverage Looker’s conversational analytics and data agent features to enable stakeholders to interact with data using natural language queries.
  • Cross-Functional Collaboration: Communicate effectively with stakeholders to understand business requirements and deliver data-driven solutions. Identify opportunities for implementing AI/ML/NLP technologies in collaboration with product, engineering, and business teams.
  • Programming & Automation: Write efficient Python code for data analysis, data processing, and automation of recurring tasks. Skilled in shell scripting and command-line tools to support data workflows and system tasks. Ensure code is well-tested and integrated into automated workflows (e.g., via Airflow job scheduling).
  • Visualization & Presentation: Create compelling visualizations and presentations to deliver analytical insights and actionable recommendations to senior management and cross-functional teams. Tailor communication of complex analyses to diverse audiences.
  • Innovation & Best Practices: Stay up-to-date with industry trends, emerging tools, and best practices in data engineering and analytics (with a focus on dbt features, Snowflake’s latest offerings and BI innovations). Develop and implement innovative ideas to continuously improve our analytics stack and practices.

What You Bring

  • Education: Bachelor’s degree in Computer Science, Statistics, or a related field; Master’s degree preferred.
  • Experience: 2+ years of experience in data analytics or a related field, with significant exposure to AI and Machine Learning applications in analytics.
  • SQL Expertise: Advanced SQL skills with experience in writing and optimizing complex queries on large-scale datasets.
  • dbt Proficiency: Hands-on experience with dbt (Data Build Tool) and its features for building, testing, and documenting data models.
  • Data Modeling: Expert-level knowledge of data modeling and data warehouse concepts (e.g., star schema, normalization, slowly changing dimensions).
  • Snowflake & AI Capabilities: Experience with Snowflake’s Data Cloud platform and familiarity with its advanced AI capabilities (Snowflake Intelligence – Cortex Analyst, Cortex Agents, Cortex Search, AISQL, etc.) is highly preferred.
Source · Tucows Inc.First seen 7 NovOriginal ↗