
Senior Data Pipeline Architect
5 days ago
Unlock the Power of Data Engineering
We're seeking an accomplished Data Engineer to champion data-driven initiatives and deliver high-quality solutions.
This pivotal role involves designing, building, and optimizing scalable pipelines using Spark, PySpark, and SQL, collaborating with data scientists and business stakeholders to drive business value.
- Design and develop efficient ETL workflows and data pipelines utilizing Spark, PySpark, and SQL.
- Process large datasets leveraging Spark and SQL, ensuring data quality and performance.
- Build and maintain real-time streaming applications using Spark Streaming/Kafka, driving insights from complex data sets.
- Collaborate with cross-functional teams to integrate AI/ML models into production, enhancing business outcomes.
- Develop and implement robust data transformations, streamlining data processing and analysis.
The ideal candidate will possess in-depth knowledge of Python, Spark, and PySpark, backed by hands-on experience in ETL pipeline development, real-time streaming, and data transformation. Additionally, familiarity with performance tuning (partitioning, caching, broadcast joins) and deployment on cloud platforms (AWS, Azure, GCP, Databricks) is essential.
Key Requirements:
Technical Skills: Python, Spark, PySpark, ETL, Real-Time Streaming, Data Transformation
Deployment Platforms: AWS, Azure, GCP, Databricks
Tools and Technologies: Kafka, Flume, Kinesis, Parquet, Avro, ORC
Soft Skills: Collaboration, Communication, Problem-Solving, Adaptability
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