Lead Data Engineer

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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👻 Ghost score 13%

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Aimpoint Digital

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

💼 Consulting

Artificial Intelligence • Analytics • Consulting

Aimpoint Digital is a market-leading analytics, data engineering, operations research, and Artificial Intelligence advisory and solution engineering firm. It empowers organizations to unlock value from data by providing strategic guidance, developing state-of-the-art AI solutions, and implementing cutting-edge analytics applications. Aimpoint Digital partners with various companies to enhance operations, drive data-driven decisions, and maximize ROI through personalized data strategies and optimization solutions.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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