Greetings Everyone,
We are Photon, one of the world's largest Digital Platform Engineering companies providing a unique combination of Strategy Consulting, Creative Design and Technology Services to a wide range of customers.
We are a high growth organization serving over 40% of Fortune 100 companies and truly believe that our people make the world of difference for our clients and our business. With Photon, you get the opportunity to learn and grow, build deep digital/technical expertise, and achieve your professional and personal aspirations.
Check out our introduction video - https://vimeo.com/708402190/6927030bf6
Designation: Spark Data Onboarding Engineer
Location: Jersey City, NJ
Job Type: Fulltime Only
We are seeking a skilled PySpark Data Engineer to join our team and drive the development of robust data processing and transformation solutions within our data platform. You will be responsible for designing, implementing, and maintaining PySpark-based applications to handle complex data processing tasks, ensure data quality, and integrate with diverse data sources. The ideal candidate possesses strong PySpark development skills, experience with big data technologies, and the ability to work in a fast-paced, data-driven environment.
Key Responsibilities:
Data Engineering Development:
- Design, develop, and test PySpark-based applications to process, transform, and analyze large-scale datasets from various sources, including relational databases, NoSQL databases, batch files, and real-time data streams.
- Implement efficient data transformation and aggregation using PySpark and relevant big data frameworks.
- Develop robust error handling and exception management mechanisms to ensure data integrity and system resilience within Spark jobs.
- Optimize PySpark jobs for performance, including partitioning, caching, and tuning of Spark configurations.
Data Analysis and Transformation:
- Collaborate with data analysts, data scientists, and data architects to understand data processing requirements and deliver high-quality data solutions.
- Analyze and interpret data structures, formats, and relationships to implement effective data transformations using PySpark.
- Work with distributed datasets in Spark, ensuring optimal performance for large-scale data processing and analytics.
Data Integration and ETL:
- Design and implement ETL (Extract, Transform, Load) processes to ingest and integrate data from various sources, ensuring consistency, accuracy, and performance.
- Integrate PySpark applications with data sources such as SQL databases, NoSQL databases, data lakes, and streaming platforms