Lead Data Engineer

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Serve as a reliable advisor on data and AI for clients, ranging from data owners and analytics users to executive stakeholders.

• Convert business inquiries into AI-ready data architectures.

• Independently tackle intricate data engineering challenges across various industries or oversee small project teams.

• Design and deploy AI-optimized data platforms, such as cloud data warehouses, lakehouses, ETL/ELT pipelines, orchestration jobs, and analytical layers.

• Develop and enhance semantic and analytical layers for Snowflake Cortex, Databricks Genie, BI platforms, and AI copilots.

• Utilize Snowflake, Databricks, dbt, Fivetran, and cloud-native orchestration frameworks to provide scalable solutions.

• Construct ELT/ETL pipelines for structured, semi-structured, and unstructured data.

• Create data models that focus on metrics layers, knowledge graphs, and semantic consistency.

• Write production-ready SQL, Python, and Spark code, adhering to Git and CI/CD best practices.

• Employ AI-assisted methodologies for data exploration, quality assurance, schema generation, documentation, lineage tracking, and transformation acceleration.

• Contribute to the AI-centric data engineering and infrastructure practice, including the development of internal accelerators, patterns, and client-ready architectures.

• Collaborate with analytics, data science, and ML teams to implement AI-enabled analytics, features, and inference pipelines.

• Engage in practice enhancement, business development, and innovative company initiatives.

• Note: This position does not include the development of machine learning models or algorithms.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent experience.

• Proven experience in managing stakeholders and collaborating with customers.

• Excellent written and verbal communication skills.

• Over 5 years of experience with relational databases and query languages.

• More than 5 years of experience in building production data pipelines for structured, semi-structured, and unstructured data.

• At least 5 years of experience in data modeling, including star schema, entity-relationship, or data vault methodologies.

• More than 5 years of experience writing clean, maintainable, and robust code in Python, Scala, Java, or similar languages.

• Preferred: over 5 years of experience with dbt Core/Cloud.

• Experience in enabling or expediting data platform engineering workflows using AI tools such as Codex, Claude, Copilot, Snowflake Cortex Code, and/or Databricks Genie Code is preferred.

• Ability to independently manage a workstream and oversee a small team of 1–2 individuals.

• Strong knowledge of software engineering concepts and best practices.

• Required: DevOps experience.

• Required: Experience with cloud data warehouses such as Databricks or Snowflake.

• Strongly preferred: One or more Databricks or Snowflake certifications.

• Preferred: Experience with cloud ETL/ELT tools like Fivetran, dbt, Matillion, Informatica, or Talend.

• Preferred: Familiarity with cloud platforms such as AWS, Azure, or GCP, and container technologies like Docker or Kubernetes.

• Preferred: Experience with Apache Spark.

• Preferred: Experience preparing data for analytics and adhering to a data science workflow.

• Strongly preferred: Consulting experience.

• Willingness to travel.

🏝️ Benefits

• Fully remote work opportunities within the US and Colombia.

• Atlanta-based applicants have the option to work at the headquarters in Sandy Springs, Georgia, or in offices located in London and Medellín.

• Professional certifications are supported and encouraged.

• Opportunity to contribute to internal accelerators, patterns, and client-ready architectures.

• Opportunity to lead small-team project delivery and participate in practice development.

• Willingness to travel.