onsite
Senior Analytics Engineer - Alpaca
Data Engineer
Lead end‑to‑end analytics engineering, building scalable data pipelines and models on AWS, leveraging Python, SQL, Spark and Airflow to deliver actionable insights for institutional clients.
About the role
Key Responsibilities
- Design, develop, and maintain large‑scale data pipelines using Python, SQL, and Apache Spark on AWS.
- Implement and orchestrate workflows with Airflow, ensuring reliability and observability.
- Collaborate with data scientists and product teams to translate business requirements into robust data models.
- Optimize query performance and storage costs across Redshift, S3, and other data stores.
- Document architecture, data lineage, and best practices for the analytics engineering team.
Requirements
- 5+ years of experience in data engineering or analytics engineering roles.
- Proficiency in Python, SQL, and experience with Spark or similar big‑data frameworks.
- Hands‑on experience with AWS services (Redshift, S3, Glue, EMR, Lambda).
- Strong understanding of data modeling, ETL design, and workflow orchestration.
- Excellent problem‑solving skills and ability to communicate complex concepts to cross‑functional teams.
Skills
pythonsqlawsapache sparkairflow