Senior Data Engineer

🕒 August 10

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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👻 Ghost score 17%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• Become a trusted data and AI advisor to clients, translating business questions into AI-ready data architectures • Work independently as part of a small team to solve 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 and evolve semantic and analytical layers supporting Snowflake Cortex, Databricks Genie, BI platforms, and AI copilots • Deliver scalable solutions using Snowflake, Databricks, dbt, Fivetran, and cloud-native orchestration frameworks • Engineer ELT/ETL pipelines for structured, semi-structured, and unstructured data • Design modern 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 to internal accelerators, engineering patterns, and client-ready architectures • Collaborate with analytics, data science, and ML teams to productionize AI-enabled analytics, features, and inference pipelines • Work independently on client engagements, contribute to practice development and business development, and propose innovative initiatives

🎯 Requirements

• Degree educated in Computer Science, Engineering, Mathematics, or equivalent experience • Experience partnering with business stakeholders and explaining technical concepts clearly • Knowledge of modern data engineering and AI trends, including LLM-powered analytics, semantic layers, vectorized data access, and metadata-driven architectures • Strong written and verbal communication skills • 3+ years working with relational databases and query languages • 3+ years building production data pipelines across structured, semi-structured, and unstructured data • 3+ years of data modeling, such as star schema and entity-relationship modeling • 3+ years writing clean, maintainable, and robust code in Python, Scala, Java, or similar languages • 2+ years of experience with dbt Core and/or dbt Cloud preferred • Experience with AI tools such as Codex, Claude, Copilot, Snowflake Cortex Code, and/or Databricks Genie Code preferred • Ability to work independently and own end-to-end delivery from design through production • Expertise in software engineering concepts and best practices • DevOps experience preferred • Experience with cloud data warehouses such as Databricks, Snowflake, Google BigQuery, AWS Redshift, or Microsoft Synapse 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 and 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

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