Data Engineer with Spark
Bentonville, AR (Day 1 On-Site)
Long Term
We are seeking a Data Engineer with Spark & Streaming skills to build 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.
Must Have Skills
Skill 1 8+ years of experience in Python, SQL, and potentially Scala/Java
Skill 2 Big Data: Expertise in Apache Spark (Spark SQL, DataFrames, Streaming).
Skill 3- 4+ Years in Google Cloud Platform
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 Google Cloud Platform, Azure data services.
Databases: Knowledge of data warehousing (Snowflake, Redshift) and NoSQL databases.
Tools: Experience with Airflow, Databricks, Docker, Kubernetes is a plus.
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.
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