
Scaling Big Data with Apache Spark
2 weeks ago
This position involves designing, developing and maintaining large-scale data pipelines using Apache Spark and AWS services.
Responsibilities:- Data Pipeline Design: Develop robust ETL/ELT pipelines on AWS using Spark and PySpark.
- Performance Optimization: Optimize large-scale data processing workflows for performance and reliability.
- AWS Services Integration: Work with AWS services such as Glue, EMR, S3, Lambda, and Redshift.
- Data Quality Assurance: Ensure data quality, governance, and security across all pipelines.
- Experience: 6+ years of experience in data engineering.
- Technical Skills: Strong proficiency in Spark, PySpark, SQL, and Python.
- AWS Knowledge: Hands-on experience with AWS data services.
- Distributed Computing: Solid understanding of distributed computing and data architecture.
- Problem-Solving: Excellent problem-solving and communication skills.
- CICD: Experience with CI/CD for data pipelines.
- Data Architecture: Familiarity with data lake and data warehouse architectures.
We offer competitive compensation and opportunities for professional growth. If you are passionate about working with cutting-edge technology and driving innovation, please submit your application.
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