Data Engineer GCP & Scala - W2
Job in
Bentonville, Benton County, Arkansas, 72712, USA
Listed on 2026-03-12
Listing for:
Saransh Inc
Full Time
position Listed on 2026-03-12
Job specializations:
-
IT/Tech
Data Engineer, Big Data, Cloud Computing, Database Administrator
Job Description & How to Apply Below
Role:
Data Engineer with GCP & Scala - Only W2
Location:
Bentonville, AR (Onsite from Day
1)
Job Type: W2 Contract
Only W2 - No C2C (or) Third-party candidates
Mandatory Areas
Must Have Skills – Data Engineer with Scala
- Scala, Spark, Python, SQL, Bigdata, Hadoop
GCP data tools:
Big Query, Dataproc, Vertex AI, Pub/Sub, Cloud Functions
PySpark, Python, Spark
SQL, and data modeling
Total IT Experience – Minimum 8 Years
GCP - 4+ years of recent GCP experience
DescriptionWe are seeking a Data Engineer with Spark & SCALA.Streaming skills builds real-time, scalable data pipelines using tools like Spark, Kafka, and cloud services (GCP) to ingest, transform, and deliver data for analytics and ML.
Responsibilities- 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 (Big Query), 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 alerting systems to ensure data accuracy and consistency.
Skills & Qualifications
- Programming:
Strong proficiency in Python, SQL, and potentially Scala/Java. - Big Data:
Expertise in Apache Spark (Spark SQL, Data Frames, 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 No
SQL databases. - Tools:
Experience with Airflow, Databricks, Docker, Kubernetes is a plus.
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