remote
Data Engineer - Parsons
Data Engineer
Design, build, and maintain scalable data pipelines and warehouses, applying advanced statistical methods and cloud technologies to transform complex datasets into actionable insights.
About the role
Key Responsibilities
- Design, develop, and optimize end‑to‑end data pipelines using Python, SQL, and Apache Spark.
- Implement ETL processes to ingest, cleanse, and transform large‑scale datasets from diverse sources.
- Build and maintain data warehouses on AWS services (Redshift, S3, Glue) ensuring high availability and performance.
- Apply statistical and mathematical techniques to analyze data quality, support modeling, and generate actionable insights.
- Collaborate with data scientists, analysts, and business stakeholders to define data requirements and deliver reliable data solutions.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field with 3+ years of data engineering experience.
- Proficiency in Python, SQL, and big‑data frameworks such as Apache Spark.
- Hands‑on experience with AWS data services (Redshift, S3, Glue, Lambda) and containerization (Docker).
- Strong understanding of data modeling, schema design, and ETL best practices.
- Ability to apply statistical methods to solve complex data problems and communicate findings clearly.
Skills
pythonsqlawsapache spark