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# Data Engineer

- **Company:** UST Inc
- **Location:** Sunnyvale, CA, United States
- **Experience:** Experienced
- **Salary:** $72,000.0 - $108,000.0
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), Airflow, Big Data, BigQuery, Cloud Computing, Computer Programming, Databases, Data Architecture, Data Validation, Extract Transform Load (ETL), Data Warehousing, Apache Hive, Python (Programming Language), NoSQL, Performance Tuning, SQL Databases, Data Streaming, Azure Data Factory, Snowflake, Apache Spark, Data Lakes, Pyspark, Kubernetes, Information Technology, Apache Flink, Real Time Data, Apache Kafka, Video Streaming, Data Pipelines, Docker, Databricks
- **Published:** August 22, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/88119667/1

## About the Role

* Programming: Strong proficiency in Python, SQL, and potentially Scala/Java.

 * Big Data: Expertise in Apache Spark (Spark SQL, DataFrames, Streaming).

 * Streaming: Experience with messaging queues like Apache Kafka, or Pub/Sub.

 * Cloud: Familiarity with GCP, Azure data services.

 * Databases: Knowledge of data warehousing (Snowflake, Redshift) and NoSQL databases.

 * Tools: Experience with Airflow, Databricks, Docker, Kubernetes is a plus. Experience Level

 * Total IT Experience - Minimum 8 years

 * GCP - 4 + years of recent GCP experience

 * Bachelor's degree in computer science, Information Technology, Engineering, or an equivalent technical discipline.

 * Experience Range: 6+ Years

Compensation can differ depending on factors including but not limited to the specific office location, role, skill set, education, and level of experience. UST provides a reasonable range of compensation for roles that may be hired in various U.S. markets as set forth below.

## Description

* As a Senior Data Engineer, you will Design, develop, and maintain ETL/ELT data pipelines for batch and real-time data ingestion, transformation, and loading using Spark (PySpark/Scala) and streaming technologies (Kafka, Flink).

 * Build and optimize scalable data architectures, including data lakes, data warehouses (BigQuery), and streaming platforms.

 * Performance Tuning: Optimize Spark jobs, SQL queries, and data processing workflows for speed, efficiency, and cost-effectiveness.

 * Data Quality: Implement data quality checks, monitoring, and ing systems to ensure data accuracy and consistency.

This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.


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