Lead Data Engineer

Aimpoint Digital

. Advise clients—including data owners, analytic users, and executive stakeholders—on AI-ready data architectures .

Posted 10/22/2026full-timeRemote • United States, ColombiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI-optimized data architectures, including cloud data warehouses and ETL/ELT pipelines. Proficient in data modeling, stakeholder management, and delivering scalable data engineering solutions using tools like Snowflake and Databricks.

Highest-signal resume keywords

Data Architecture DesignETL/ELT Pipeline EngineeringData Modeling ExpertiseCloud Data WarehousingStakeholder Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonSparkData ModelingProduction Data PipelinesRelational DatabasesData Engineering WorkflowsAI-Assisted TechniquesDevOps Best PracticesCloud Data Platforms

Soft Skills

Written CommunicationVerbal CommunicationTeam LeadershipCollaborationStakeholder Management

Tools & Technologies

SnowflakeDatabricksDbtFivetranAWSAzureGCPDockerKubernetesMatillion

Certifications & Qualifications

Databricks CertificationSnowflake Certification

Industry Keywords

Data EngineeringAI-Optimized SolutionsCloud ETL/ELTAnalyticsMachine Learning

Tech Stack

Tools & technologies

ApacheAWSAzureCloudDockerETLGoogle Cloud PlatformInformaticaJavaKubernetesMatillionPythonScalaSparkSQLVault

About the role

Key responsibilities & impact

Advise clients—including data owners, analytic users, and executive stakeholders—on AI-ready data architectures
Translate business questions into analytical and data engineering solutions
Work independently or lead small teams on complex data engineering use cases across industries
Design and implement AI-optimized data platforms, including cloud data warehouses, lakehouses, ETL/ELT pipelines, orchestration jobs, and analytical layers
Build semantic and analytical layers for Snowflake Cortex, Databricks Genie, BI platforms, and AI copilots
Use Snowflake, Databricks, dbt, Fivetran, and cloud-native orchestration frameworks to deliver scalable solutions
Engineer ETL/ELT pipelines for structured, semi-structured, and unstructured data
Design data models emphasizing metrics layers, knowledge graphs, and semantic consistency
Write production-ready SQL, Python, and Spark code using Git and CI/CD best practices
Apply AI-assisted techniques for data exploration, quality checks, schema generation, documentation, lineage, and transformation acceleration
Contribute internal accelerators, patterns, and client-ready architectures to the data engineering and infrastructure practice
Collaborate with analytics, data science, and ML teams to productionize AI-enabled analytics, features, and inference pipelines
Support practice development, business development, and innovative company initiatives
Travel as needed; machine-learning model or algorithm development is not part of the role

Requirements

What you’ll need

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 production data pipelines across structured, semi-structured, and unstructured data
5+ years of data modeling, including star schema, entity-relationship, or data vault
5+ years writing clean, maintainable, and robust code in Python, Scala, Java, or similar languages
5+ years of experience with dbt Core/Cloud preferred
Experience enabling data platform engineering workflows with AI tools such as Codex, Claude, Copilot, Snowflake Cortex Code, and/or Databricks Genie Code preferred
Ability to manage an individual workstream independently and lead a small 1–2 person team
Expertise in software engineering concepts and best practices
DevOps experience required
Experience with cloud data warehouses; Databricks or Snowflake required
One or more Databricks or Snowflake certifications strongly preferred
Experience with cloud ETL/ELT tools such as Fivetran, dbt, Matillion, Informatica, or Talend preferred
Experience with AWS, Azure, or GCP and container technologies such as Docker or Kubernetes preferred
Experience with Apache Spark preferred
Experience preparing data for analytics and following a data science workflow preferred
Consulting experience strongly preferred
Willingness to travel

Benefits

Comp & perks

Fully remote work arrangement
Opportunity to work in the new headquarters in Sandy Springs, GA for Atlanta-based applicants