Lead Data Engineer

🕒 Agosto 25

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

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Aimpoint Digital

SiteLinkedInTodas as Vagas

51 - 200 funcionários

🤖 Inteligência Artificial

💼 Consultoria

Artificial Intelligence • Analytics • Consulting

A Aimpoint Digital é uma empresa líder de mercado em consultoria e engenharia de soluções em análises, engenharia de dados, pesquisa operacional e Inteligência Artificial. Ela capacita organizações a desbloquear valor a partir de dados, fornecendo orientação estratégica, desenvolvendo soluções de IA de ponta e implementando aplicações analíticas avançadas. A Aimpoint Digital colabora com diversas empresas para aprimorar operações, promover decisões baseadas em dados e maximizar o retorno sobre o investimento por meio de estratégias de dados personalizadas e soluções de otimização.

Descrição

• Advise clients, including data owners, analytics users, and executive stakeholders, on translating business questions into AI-ready data architectures • Independently solve complex data engineering use cases across multiple industries as part of a small team • Design and implement AI-optimized data platforms, including cloud data warehouses, lakehouses, ETL/ELT pipelines, orchestration jobs, and analytical layers • Build and evolve semantic and analytical layers supporting Snowflake Cortex, Databricks Genie, BI platforms, and emerging AI copilots • Deliver scalable solutions using Snowflake, Databricks, dbt, Fivetran, and cloud-native orchestration frameworks • Engineer modern ELT/ETL pipelines for structured, semi-structured, and unstructured data • Design data models emphasizing metrics layers, knowledge graphs, and semantic consistency for AI consumption • 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 to the AI-forward data engineering and infrastructure practice, including internal accelerators, patterns, and client-ready architectures • Collaborate with analytics, data science, and ML teams to productionize AI-enabled analytics, features, and inference pipelines • Lead small-team project delivery, support practice development and business development, and contribute innovative ideas • Not responsible for developing machine learning models or algorithms

🎯 Requisitos

• Degree educated in Computer Science, Engineering, Mathematics, or equivalent experience • Experience 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, such as star schema, entity-relationship, or data vault • 5+ years writing clean, maintainable, and robust code in Python, Scala, Java, or similar languages • 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 • Ability to manage an individual workstream independently and 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 cloud platforms such as 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 to drive business results preferred • Consulting experience strongly preferred • Willingness to travel

🏖️ Benefícios

• Fully remote work • Opportunity to work from headquarters in Sandy Springs, GA for Atlanta applicants • Certifications to credentialize skills • Work with modern data engineering platforms and tooling • Opportunity to contribute to internal accelerators, patterns, and client-ready architectures • Opportunity to contribute innovative ideas and initiatives to the company