Data and ML Engineer

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