• Design and develop interactive reports and dashboards using Power BI to visualize complex data sets. • Develop and optimize Power BI DAX measures to calculate key performance indicators (KPIs) and metrics. • Leverage Microsoft Power Query for data transformations and cleansing tasks. • Explore and integrate additional data sources, including those from Snowflake. • Ensure data accuracy, consistency, and reliability in all reporting outputs. • Continuously improve and optimize existing reports and dashboards based on user feedback and evolving business requirements. • Drive the adoption of reports and dashboards by monitoring report usage and customer feedback. • Perform full end-to-end development of BI reporting needs, from requirements gathering, schema creation and ultimately publishing production ready dashboards and reports. • Translate business requirements into production reports for designated internal departments and business users. • Manage designated Microsoft Teams channel and communication with business and stakeholders. • Manage Power BI Workspaces including access to specific reports utilizing RLS (Role Level Security). • Assist with updating and maintaining departmental confluence pages. • Leverage Jira ticketing system to track and update requests from the business. • Stay up-to-date with industry best practices and emerging trends in business intelligence and data visualizations. • Responsible for maintaining regular communication with designated business units on a regular basis to foster communication and set delivery expectations.

• Design, develop, and maintain complex data models in our Snowflake data warehouse. • Leverage Snowflake Intelligence features to implement conversational data queries and AI-driven insights. • Design and build advanced SQL queries to retrieve and manipulate complex data sets. • Develop, maintain, and optimize Looker dashboards and LookML to effectively communicate data insights. • Communicate effectively with stakeholders to understand business requirements and deliver data-driven solutions. • Write efficient Python code for data analysis, data processing, and automation of recurring tasks. • Create compelling visualizations and presentations to deliver analytical insights and actionable recommendations. • Stay up-to-date with industry trends, emerging tools, and best practices in data engineering and analytics.

Role Description 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. - Develop and implement innovative ideas to continuously improve our analytics stack and practices. Qualifications - Bachelor’s degree in Computer Science, Statistics, or a related field; Master’s degree preferred. - 2+ years of experience in data analytics or a related field, with significant exposure to AI and Machine Learning applications in analytics. - Advanced SQL skills with experience in writing and optimizing complex queries on large-scale datasets. - Hands-on experience with dbt (Data Build Tool) and its features for building, testing, and documenting data models. - Expert-level knowledge of data modeling and data warehouse concepts (e.g., star schema, normalization, slowly changing dimensions). - Experience with Snowflake’s Data Cloud platform and familiarity with its advanced AI capabilities is highly preferred. - Strong skills in Looker data visualization and LookML or similar BI tools. - Experience with AI agents or generative AI tools to optimize workflows and service delivery is a plus. - Experience with real-time data processing and streaming technologies for handling continuous data flows. - Proficient in Python for data analysis and manipulation, with the ability to write clean, efficient code. - Familiarity with ETL processes and workflow orchestration tools for automating data pipelines. - Experience with cloud platforms and services for data storage, compute, and deployment. - Solid understanding of code versioning and continuous integration/continuous deployment processes in a data engineering context. - Familiarity with agile development methodologies and ability to work in a fast-paced, iterative environment. - Excellent communication and presentation skills, with critical thinking and problem-solving abilities. - Experience implementing data governance best practices, ensuring data quality and consistency. Requirements - Contributions to open-source projects or active participation in data community initiatives. - Experience with applying Artificial Intelligence/Machine Learning techniques in analytics. - Solid foundation in statistics and probability, with ability to apply various modeling techniques and design A/B tests or experiments. - Knowledge of additional programming or query languages that can be applied in analytics workflows. - Certifications in relevant data technologies or cloud platforms demonstrating your expertise. Benefits - The base salary range for this position is $73,800 to $82,000. - Tucows believes in a total rewards offering that includes fair compensation and generous benefits.

• Design and develop scalable data models that power our data products • Collaborate with key stakeholders across product, engineering, operations, and data science teams • Contribute to and improve our dbt implementation and data models • Collaborate with partners across technical and non-technical teams • Support key decision makers about the state of the business • Participate in development, testing, documentation, and evangelism of core data models • Utilize analytical tools like Databricks, BigQuery, Airflow, Mode, and Tableau