Analytics Engineer, Data at Jobgether

, , Canada -

Full Time

Start Date

Immediate

Expiry Date

02 Oct, 26

Salary

150000.0

Posted On

04 Jul, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Modeling, Dimensional Modeling, dbt, BigQuery, Looker, Airflow, Semantic Layer, Analytics Engineering, Stakeholder Management, Data Pipelines, LLM Integration, Metric Governance, Data Validation, Cloud Data Warehousing, Agentic Querying

Industry

Internet Marketplace Platforms

Description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Analytics Engineer, Data based in Canada. This role sits at the intersection of analytics engineering, data modeling, and AI-enabled decision systems, focused on building the trusted data foundation that powers self-serve insights across the organization. You will act as the bridge between business stakeholders and data systems, translating ambiguous questions into well-defined, reusable metrics and scalable data models. A core part of your impact will be expanding and maintaining a semantic layer that ensures consistency, trust, and accessibility across analytics workflows. You will also help enable LLM-powered analytics experiences, ensuring data is structured and enriched for agentic querying and automated insight generation. This is a highly collaborative, builder-focused role where success is measured by how much clarity and autonomy you create for others. You will work across product, go-to-market, and leadership teams in a fully remote, AI-native environment. \n Accountabilities: Partner with product, GTM, and executive stakeholders to translate ambiguous business questions into clearly defined metrics, datasets, and analytical solutions. Own and expand the semantic/metrics layer, ensuring consistent definitions, reusable models, and trusted business logic across the organization. Design, build, and maintain scalable data models that support self-serve analytics and LLM/agent-driven querying. Improve data trust by implementing validation logic, documentation standards, and metric governance frameworks. Develop and operationalize pipelines to ingest new data sources (e.g., product usage, GTM systems) and integrate them into the analytics ecosystem. Enable AI-driven analytics workflows by structuring metadata, datasets, and metrics for consumption by LLM-based tools. Support reporting, dashboards, and curated datasets that empower internal teams to answer their own questions independently. Requirements 3+ years of experience in analytics engineering, data engineering, or a closely related role with ownership of metrics or data models used across teams. Strong expertise in SQL and data modeling (dimensional modeling, transformation pipelines, incremental models, and scalable architectures). Proven experience building or maintaining a semantic/metrics layer that is widely adopted across an organization. Hands-on experience working with cloud data warehouses (BigQuery preferred), BI tools (e.g., Looker), and modern data stacks (dbt, Airflow, or similar). Experience integrating and structuring data for AI/LLM-driven workflows or agent-based analytics tools is highly valued. Ability to build end-to-end data solutions, including ingestion, transformation, and modeling of new data sources. Strong stakeholder management skills with the ability to translate business needs into technical data requirements. A strong builder mindset focused on scalability, reuse, and enabling self-serve analytics across teams. Benefits Competitive compensation aligned with Canadian market benchmarks (approx. CAD $125,000 – $150,000 base range) Equity participation and performance-based bonus structure Fully remote work environment with flexible collaboration across time zones (EST/EDT aligned) Opportunity to work at the forefront of AI-native analytics and LLM-powered data systems Exposure to high-scale datasets and global enterprise customers Strong emphasis on ownership, autonomy, and impact-driven engineering culture Comprehensive benefits package including health coverage and additional employee perks. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1

Responsibilities

Build and maintain a trusted data foundation and semantic layer to power self-serve insights and AI-enabled decision systems. Act as a bridge between business stakeholders and data systems to translate ambiguous questions into scalable data models and metrics.