Big Data Engineer with Apache Spark Expertise
1 miesiąc temu
**Company Overview**
We are a leading global business solutions provider, Link Group. Our company is dedicated to delivering innovative solutions that transform the way businesses operate.
**Salary:** We offer a highly competitive salary of $120,000 - $180,000 per annum, depending on experience and qualifications.
**Job Description**
As a Big Data Engineer with Apache Spark expertise, you will play a key role in designing, developing, and maintaining large-scale data processing pipelines using PySpark. Your primary responsibility will be to work closely with cross-functional teams to understand data requirements and design optimal solutions.
**Key Responsibilities**
- Design, develop, and maintain ETL pipelines using PySpark to process and analyze large datasets.
- Collaborate with data engineers, data scientists, and business stakeholders to understand data requirements and design optimal solutions.
- Optimize PySpark applications for performance and scalability in distributed computing environments.
- Work with Hadoop-based data platforms and integrate with other tools like Hive, HDFS, or Kafka.
- Ensure data quality and integrity through robust validation and monitoring practices.
- Debug and resolve issues in production and pre-production environments.
- Document technical solutions and best practices.
**Technical Requirements**
- 5+ years of experience in data engineering or big data development, with a strong focus on PySpark.
- Proficiency in Python programming, with experience in libraries commonly used in data processing (e.g., Pandas, NumPy).
- Strong understanding of Apache Spark concepts: Spark Core, Spark SQL, and Spark Streaming.
- Experience with distributed data processing frameworks and working in cloud-based environments (e.g., AWS, Azure, GCP).
- Solid knowledge of big data technologies like Hadoop, Hive, HDFS, Kafka, or Airflow.
- Hands-on experience with relational and NoSQL databases (e.g., PostgreSQL, Cassandra).
- Familiarity with CI/CD pipelines and version control (e.g., Git).
**Preferred Qualifications**
- Experience with streaming data using Spark Streaming or Kafka.
- Knowledge of machine learning workflows and integration with big data pipelines.
- Understanding of containerization tools like Docker or orchestration with Kubernetes.
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