LaunchGood

Title: Data and ML Engineer Location: Canada or United Kingdom, Remote Department: Engineering Job Description: Remote | some EST overlap preferred Mission Help LaunchGood build scalable data systems and intelligent workflows that power better decision-making across the organization. This role sits at the intersection of Data Engineering, Analytics, and Machine Learning. You’ll help improve our data infrastructure, support self-serve analytics initiatives, and contribute to AI and ML-powered solutions across internal products and workflows. You’ll work closely with the Data team and cross-functional stakeholders to help modernize and scale our data ecosystem. Expectations and Responsibilities Data Engineering & Infrastructure - Build and maintain reliable data pipelines and workflows - Support improvements to data architecture, modeling, and warehouse organization - Help improve data quality, monitoring, observability, and documentation practices - Optimize queries, transformations, and warehouse performance - Support analytics engineering workflows and reusable data models ML & AI Enablement - Assist in building and operationalizing ML and AI-enabled workflows - Support predictive analytics and automation initiatives - Contribute to experimentation with LLM-powered tools and internal AI workflows - Help build scalable datasets and features for ML use cases Collaboration & Execution - Work with Product, Engineering, and business teams to support reporting and analytics needs - Translate business problems into technical solutions - Participate in code reviews, QA, and engineering best practices - Contribute to documentation and knowledge-sharing across the Data team Competencies - 2–4 years of experience in Data Engineering, Analytics Engineering, ML Engineering, or related roles - Strong SQL and Python skills - Experience working with cloud data warehouses such as BigQuery - Exposure to ML models or AI-powered workflows - Familiarity with LLMs, embeddings, or AI tooling - Familiarity with dbt or similar transformation frameworks - Experience building or maintaining data pipeline - Understanding of data modeling and analytics engineering concepts - Familiarity with APIs and automation workflows - Strong problem-solving and communication skills - Comfortable working in fast-moving and evolving environments Nice to Have - Experience with analytics tools such as PostHog, Heap, or Looker - Experience with orchestration or workflow automation tools - Startup or high-growth company experience - Interest in data quality, governance, and self-serve analytics