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.
Role:Data Engineer
Industry Type:IT Services & Consulting
Department:Data Science & Analytics
Employment Type:Full Time, Permanent
Role Category:Data Science & Machine Learning
Education
UG:Any Graduate