remote
Staff Data Engineer - John Deere
Data Engineer
Lead end‑to‑end data engineering initiatives, designing scalable pipelines on AWS, leveraging Python, SQL, Spark and Airflow to deliver high‑quality data products for advanced analytics.
About the role
Key Responsibilities
- Design, build and maintain large‑scale data pipelines on AWS, ensuring reliability, scalability and performance.
- Develop and optimize ETL processes using Python, SQL and Apache Spark to transform raw data into analytics‑ready formats.
- Implement workflow orchestration with Airflow, managing dependencies, scheduling and monitoring of data jobs.
- Collaborate with data scientists and business stakeholders to understand requirements and deliver actionable data solutions.
- Champion best practices in data quality, security, and governance across the data platform.
Requirements
- Extensive experience in data engineering, preferably in a large enterprise environment.
- Proficiency in Python, SQL, and big‑data frameworks such as Apache Spark.
- Hands‑on experience with AWS services (S3, Redshift, EMR, Glue, Lambda).
- Strong knowledge of workflow orchestration tools, especially Airflow.
- Excellent problem‑solving skills and ability to communicate complex technical concepts clearly.
Skills
pythonsqlawsapache sparkairflow