Lead Data Engineer 2026- US

Aimpoint Digital is a dynamic and fully remote AI and Data consultancy. The Lead Data Engineer will work with clients to design end-to-end analytical solutions, implement AI-optimized data platforms, and collaborate with various teams to enhance data engineering practices.

Responsibilities:

• Become a trusted data and AI advisor to our clients, from data owners and analytic users to executive stake holders helping them translate business questions into AI-ready data architectures
• Work independently as part of a small team to solve complex data engineering use-cases across a variety of industries
• Design and implement AI-optimized data platforms, including cloud data warehouses, lakehouses, ETL/ELT pipelines, orchestration jobs, and analytic layers that support LLM-driven analytics, natural language querying, and agent-based workflows
• Build and evolve semantic and analytical layers that power tools like Snowflake Cortex, Databricks Genie, BI platforms, and emerging AI Copilots
• Use modern platforms and tooling such as Snowflake, Databricks, dbt, Fivetran, and cloud-native orchestration frameworks to deliver scalable solutions, and credentialize your skills with certifications
• Engineer modern ELT/ETL pipelines that handle structured, semi-structured, and unstructured data to support AI and analytics use cases
• Design modern data models with an emphasis on metrics layers, knowledge graphs, and semantic consistency for AI consumption
• Write production-ready code in SQL, Python, and Spark, following software engineering tools and best-practices such as Git and CI/CD
• Apply AI-assisted data engineering techniques for data exploration, quality checks, schema generation, documentation, lineage, and transformation acceleration
• Contribute to the evolution of our AI-forward data engineering and infrastructure practice, including internal accelerators, patterns, and client-ready architectures
• Collaborate with analytics, data science, and ML project teams to productionize AI-enabled analytics, features, and inference pipelines

Requirements:

• Degree educated in Computer Science, Engineering, Mathematics, or equivalent experience
• Experience with managing stakeholders and collaborating with customers
• Strong written and verbal communication skills required
• 5+ years working with relational databases and query languages
• 5+ years building data pipelines in production and ability to work across structured, semi-structured and unstructured data
• 5+ years data modeling (e.g. star schema, entity-relationship, data vault)
• 5+ years writing clean, maintainable, and robust code in Python, Scala, Java, or similar coding languages
• Ability to manage an individual workstream independently and ability to manage a small 1-2 person team
• Expertise in software engineering concepts and best practices
• DevOps experience required
• Experience working with cloud data warehouses (Databricks or Snowflake required)
• Willingness to travel
• 5+ years' experience with dbt Core/Cloud preferred
• Experience enabling or accelerating data platform engineering workflows with AI tools such as Codex, Claude, Copilot, Snowflake Cortex Code, and/or Databricks Genie Code preferred
• 1 or more certifications in either Databricks or Snowflake strongly preferred
• Experience working with cloud ETL/ELT tools (Fivetran, dbt, Matillion, Informatica, Talend, etc.) preferred
• Experience working with cloud platforms (AWS, Azure, GCP) and container technologies (Docker, Kubernetes) preferred
• Experience working with Apache Spark preferred
• Experience preparing data for analytics and following a data science workflow to drive business results preferred
• Consulting experience strongly preferred