Note: The job is a remote job and is open to candidates in USA. RTX is seeking an experienced Python and PySpark Developer to design, build, and optimize next-generation big data pipelines. In this hybrid role, you will handle large-scale datasets, optimize distributed computing clusters, and bridge the gap between raw data ingestion and production-ready analytics.
Responsibilities
- Design and deploy robust batch and streaming ETL/ELT pipelines using PySpark and Python
- Optimize Spark jobs by tuning configurations, managing partitioning, and resolving data skew or OOM (Out of Memory) errors
- Implement modern data lakehouse architectures using Delta Lake, Iceberg, or Hudi
- Build and maintain complex workflow DAGs using orchestration tools like Apache Airflow
- Develop backend Python services or REST APIs (e.g., Fast API, Flask) to expose processed data to downstream applications
- Write clean, modular, and unit-tested code while participating in rigorous code reviews
Skills
- Must be a U.S. Citizen
- Strong proficiency in Python (OOP, concurrency, data structures) and advanced SQL
- Deep production experience with Apache Spark / PySpark (Data Frames, Spark SQL, RDDs)
- Hands-on experience with cloud data platforms like AWS (EMR, Glue), Azure (Databricks), or GCP
- Experience working with Snowflake, Big Query, Redshift, or Synapse
- Proficient with Git, Docker, and automated deployment pipelines
- PySpark MLlib or deploying Machine Learning models to production
- Familiarity with streaming technologies like Apache Kafka or Spark Structured Streaming
- Databricks Certified Data Engineer or Apache Spark Developer certifications
Benefits
- Medical, dental, and vision insurance
- Three weeks of vacation for newly hired employees
- Generous 401(k) plan that includes employer matching funds
- Participation in the Employee Scholar Program (ESP)
- Life insurance and disability coverage
- Employee Assistance Plan, including up to 8 free counseling sessions
Company Overview