Note: The job is a remote job and is open to candidates in USA. 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
Skills
- 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
Benefits
- Fully remote work within the US
- Atlanta applicants will have the opportunity to work from headquarters in Sandy Springs, GA
- Credentialize your skills with certifications
Company Overview