Posted:3 weeks ago|
Platform:
On-site
Full Time
We are looking for Senior data engineers who have the right attitude, aptitude, skills, empathy, compassion, and hunger for learning. Build products in the data analytics space.
● Develop and manage robust ETL pipelines using Apache Spark (Scala)
● Understand Spark concepts, performance optimization techniques, and governance tools
● Develop a highly scalable, reliable, and high-performance data processing pipeline to extract, transform, and load data from various systems to the Enterprise Data Warehouse/Data Lake/Data Mesh hosted on AWS or Azure
● Collaborate cross-functionally to design effective data solutions
● Implement data workflows utilizing AWS Step Functions or Azure Logic Apps for efficient orchestration.
● Monitor, troubleshoot, and optimize pipeline performance and data quality
● Maintain high coding standards and produce thorough documentation. Contribute to high-level (HLD) and low-level (LLD) design discussions
● Minimum 7 years of progressive experience building solutions in Big Data environments
● Have a strong ability to build robust and resilient data pipelines which are scalable, fault tolerant, and reliable in terms of data movement
● 3+ years of hands-on expertise in Python, Spark, and Kafka
● Strong command of AWS or Azure services
● Strong hands-on capabilities on SQL and NoSQL technologies
● Sound understanding of data warehousing, modeling, and ETL concepts
● Familiarity with High-Level Design (HLD) and Low-Level Design (LLD) principles
● Excellent written and verbal communication skills
Coditas
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