9 InfoService Jobs
Data Engineer - Scala/Python/Java (3-5 yrs)
InfoService
posted 2mon ago
Flexible timing
Key skills for the job
Responsibilities :
- Data Ingestion & Processing : Design and implement efficient data pipelines using big data frameworks (e.g, Spark) for ingesting, transforming, and processing large datasets.
- Programming Powerhouse : Utilize your strong coding skills in Scala (preferred), Python, or Java to develop high-performance and scalable data processing solutions.
- SQL Master : Demonstrate expertise in SQL for efficient data querying, manipulation, and analysis from various data sources.
- Big Data Landscape : Experience with popular big data frameworks like Spark or similar tools (Flink, Kafka, NoSQL) to manage and process large data volumes.
- Large Data Experience : Proven experience working with very large datasets, preferably within the DTC (Direct-to-Consumer) domain or similar large-scale data environments.
- Cloud Savvy : Experience with cloud platforms (AWS, GCP, Azure) for deploying and managing big data infrastructure is a valuable asset.
- Data Quality Champion : Ensure data quality and consistency throughout the data pipeline, implementing robust data validation and cleansing processes.
- Collaboration & Communication : Work effectively in a collaborative team environment, communicating technical concepts clearly to both technical and non-technical stakeholders.
Technical Skills & Requirements :
- Programming Expertise : Strong coding skills in Scala (preferred), Python, or Java, with a solid understanding of object-oriented programming principles.
- Big Data Frameworks : Familiarity with big data frameworks (e.g, Spark) and experience with data ingestion, processing, and analytics tools.
- SQL Proficiency : Demonstrated expertise in SQL for querying and manipulating data from relational and non-relational databases.
- Large Data Experience : Proven experience working with and processing very large datasets efficiently.
- Cloud Platforms : Familiarity with cloud platforms (AWS, GCP, Azure) for data infrastructure management (a plus).
- Data Pipelines : Experience designing and implementing scalable and maintainable data pipelines
Functional Areas: Software/Testing/Networking
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