Role: Data Engineer (Python, Scala, SQL)
Location: Bentonville, AR (Onsite from Day 1)
Job Type: W2 Contract
Note: Only W2 - No C2C (or) Third-party candidates
Mandatory Areas:
- 8+ years of experience in Python, SQL, and potentially Scala/Java
- Big Data: Expertise in Apache Spark (Spark SQL, DataFrames, Streaming).
- 4+ Years in GCP
Description:
We are seeking a Data Engineer with Spark & Streaming skills that 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:
- 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 alerting systems to ensure data accuracy and consistency.
Required Skills & Qualifications:
- 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.