• 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

• Serving as a data architect for Monzo’s Borrowing data, contributing to the design and scalability of data models that measure the performance of our product suite. • Develop robust data models downstream of backend services, primarily in BigQuery, to support internal reporting, machine learning, large language models, as well as financial and regulatory use cases. • Be a key voice in shaping and maintaining best practices for our Data Warehouse, including source data payload design, logical data modelling, implementation, metadata, and testing standards. • Collaboratively set standards and work with data across Monzo, fostering knowledge sharing and continuously improving data practices. • Contribute to prioritising data governance issues, ensuring a comprehensive approach to data integrity and compliance. • Being a key technical leader who’s able to champion central platform initiatives that aim to elevate the data standards across Borrowing and beyond.