Data Engineer Spark & SCALA Our W2

Role:
Data Engineer with Spark & SCALA on Our W2

Location:

Bentonville AR

Onsite Requirement: Y

Number of days onsite: 5 Days

• Must Have Skills – Data Engineer with Scala
• Skill 1 – Scala, Spark, Python, SQL, Bigdata, Hadoop
• Google Cloud Platform data tools – Big Query, Dataproc, Vertex AI, Pub/Sub, Cloud Functions
• Skill 2 – PySpark, Python, Spark
  
  SQL, and data modeling

Only W2 Candidates required, No glider needed for this role

We are seeking a Data Engineer with Spark & SCALA;
Streaming skills builds real-time, scalable data pipelines using tools like Spark, Kafka, and cloud services (Google Cloud Platform) to ingest, transform, and deliver data for analytics and ML.

• 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.

• 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 Google Cloud Platform, Azure data services.
• Databases:
  Knowledge of data warehousing (Snowflake, Redshift) and No
  
  SQL databases.
• Tools:
  Experience with Airflow, Databricks, Docker, Kubernetes is a plus.
• Experience Level: Total IT Experience – Minimum 8 Years.
• Google Cloud Platform – 4+ years of recent GCP experience.