Senior Analytics Engineer

Join Avison Young’s Data Architecture team as a Senior Analytics Engineer, where you will own and scale our analytics layer in Snowflake using dbt. This is a hands‑on leadership role focused on building high‑quality, business‑aligned data models that power reporting, analytics, and data products across the organization. You will act as a player‑coach, balancing hands‑on development with leadership of other engineers, while partnering closely with business stakeholders to define metrics, data models, and semantic consistency across the company. Your work will directly enable better decision‑making by ensuring data is not just available, but trusted, well‑structured, and meaningful. This role focuses on analytics engineering and data modeling, not traditional pipeline‑heavy data engineering. We are looking for someone who understands the why behind the data, not just the how. What we value in a business analyst: Customer-focused: You prioritize building data products and models that are intuitive, trusted, and drive real business outcomes. Attention to detail: You ensure data accuracy, consistency, and quality across complex transformations and models. Diverse thoughts: You collaborate effectively, incorporate feedback, and value multiple perspectives in shaping data solutions. Team player & leader: You lead by example—mentoring others, setting standards, and contributing hands‑on alongside your team. Pragmatic: You balance speed and quality, making smart trade‑offs without compromising long‑term maintainability. Data product mindset: You treat datasets as products, with clear ownership, definitions, and accountability. Global teammate: Comfortable working in a collaborative, distributed team environment. The base salary is aligned with market data and is estimated between $93,000 to $120,000 with the ability to achieve additional compensation through bonus. This salary range reflects base compensation for the position across all US locations. Within this range, individual pay is determined by work location and other factors, including relevant education/training, experience, and internal equity. Responsibilities Analytics Engineering & Data Modeling (Core Focus): Design, develop, and maintain scalable, business‑aligned data models in Snowflake using dbt (staging, intermediate, marts layers) Define and enforce semantic consistency, including metrics, dimensions, and KPIs across the organization Build and manage dbt projects, including models, tests, documentation, and lineage Design, deploy, and maintain Snowflake Cortex Search and semantic models to provide high‑quality, governed data structures for LLM‑powered applications and AI initiatives Oversee development operations and deployments of the data platform Translate business requirements into well‑structured, reusable data models Implement data quality testing, validation, and documentation to ensure trusted data Optimize query performance and transformation efficiency in Snowflake Establish and enforce data modeling standards, best practices, and design patterns Develop reusable analytics components to accelerate data product development Data Product & Stakeholder Engagement: Partner with business stakeholders to define metrics, KPIs, and data definitions Ensure alignment between business needs and technical implementations Contribute to the development of data products and semantic layers that support analytics and reporting Drive adoption and usability of data models across analytics and business teams Leadership & Team Responsibilities (Player-Coach): Lead and mentor a small team of analytics/data engineers Set standards for dbt development, code reviews, testing, and documentation Contribute hands‑on to development (~60–70%) while guiding team delivery Drive team productivity, technical direction, and project execution Support Agile processes, including backlog prioritization and sprint planning Coordination & Delivery: Gather and refine business requirements for data initiatives Translate business needs into clear technical requirements and user stories Support deployment, environment management, and release processes Ensure high‑quality delivery through testing, validation, and stakeholder alignment Qualifications 5+ years of experience in analytics engineering, data engineering, or related roles Strong expertise in SQL and data warehousing concepts Proven experience with dbt and Snowflake (required) Experience building and maintaining analytics‑ready data models and transformations Demonstrated ability to lead projects or mentor team members in a player‑coach capacity Experience with data quality, testing frameworks, and documentation practices Familiarity with Airflow / Astronomer or similar orchestration tools Experience working with data pipelines, ETL/ELT processes, and cloud data platforms Strong analytical thinking and ability to connect data solutions to business outcomes Bachelor’s degree in Information Technology, Business, or a related field, or equivalent experience Nice to have: Experience in commercial real estate, geospatial data, or location‑based analytics Experience building data products or semantic layers for BI tools #J-18808-Ljbffr