Aws Data Engineer

Job Description

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.