
Data Engineer
4 weeks ago
We are looking for data engineers who have the right attitude, aptitude, skills, empathy,
compassion, and hunger for learning. Build products in the data analytics space. A passion
for shipping high-quality data products, interest in the data products space; curiosity about
the bigger picture of building a company, product development and its people.
Roles and Responsibilities
- Develop and manage robust ETL pipelines using Apache Spark (Scala)
- Understand park 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
- Collaborate cross-functionally to design effective data solutions
- Implement data workflows utilizing AWS Step Functions for efficient orchestration. Leverage AWS Glue and Crawler for seamless data cataloging and automation
- 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
Technical Skills
- Minimum 3 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 services like EMR, Redshift, Step Functions, AWS Glue, and AWS Crawler.
- 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.
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