Senior Data Engineer

About the role

The Senior Data Engineer works remotely across North America as the lead engineer on client engagements, handling everything from data and AI‑readiness audits to building production data platforms, making data AI‑ready, providing fractional data leadership, and owning the client relationship with direct founder collaboration.

About the company

Aeolus Data Solutions is a boutique, founder‑led data engineering practice serving startups and scale‑ups across North America, designing, building, and auditing production data pipelines and AI‑ready foundations while applying Big Tech engineering discipline such as CI/CD, automated testing, and infrastructure‑as‑code.

Requirements

• 5+ years building and operating production data pipelines with ownership of data infrastructure
• Deep experience with the modern data stack: dbt, at least one cloud warehouse/lakehouse (Snowflake, Databricks, or BigQuery), an orchestrator (Airflow, Dagster, or Prefect), a major cloud platform (AWS, GCP, or Azure), and strong Python and SQL skills
• Software‑engineering discipline applied to data: version control, automated testing (dbt tests, Great Expectations), CI/CD, and infrastructure‑as‑code using Terraform
• Ability to quickly ramp on messy, unfamiliar systems and solve real‑world data quality problems in a consulting context
• Strong client‑facing communication skills, able to explain technical trade‑offs to non‑engineers and produce clear audit reports
• Self‑directed with high ownership, thriving in a small team without ticket‑assignment structures
• Nice to have: experience with RAG/LLM data pipelines (chunking, embeddings, vector databases, retrieval quality)
• Nice to have: warehouse cost optimization/FinOps expertise (query tuning, clustering, spend containment)
• Nice to have: background at Big Tech scale or high‑growth data teams
• Nice to have: prior consulting, agency, or fractional/embedded experience
• Nice to have: relevant certifications such as dbt, SnowPro, or Databricks