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 effective 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 robust 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.
Solid 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

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