AWS Data Engineer - Face to Face client interview

AWS Data Engineer

Location: Denver, CO (Onsite)

Iinterview mode:  One video round tech with Implementor, two tech rounds with client - one video tech round & final int-person tech round

Job Description:

We are looking for an experienced Data Engineer with strong expertise in ETL, SQL, AWS, and Apache Spark/EMR to design, develop, and optimize scalable data pipelines and data processing solutions. The ideal candidate will have hands-on experience building cloud-based data platforms and working with large-scale datasets. Key Responsibilities Design, develop, and maintain robust ETL/ELT data pipelines for large-scale data processing. Develop complex and optimized SQL queries, stored procedures, and data transformations. Build and optimize distributed data processing applications using Apache Spark/PySpark. Develop and manage big-data workloads using AWS EMR. Work with AWS data services including S3, Glue, Redshift, Lambda, and EMR. Perform data extraction, transformation, cleansing, validation, and loading across multiple data sources. Optimize Spark jobs, SQL queries, ETL workflows, and EMR clusters for performance and cost. Implement data quality, monitoring, logging, and error-handling mechanisms. Collaborate with data scientists, analysts, software engineers, and business stakeholders. Troubleshoot data pipeline failures and production issues. Participate in architecture discussions and contribute to scalable cloud data solutions.

Required Skills
Minimum 5+ years of experience in Data Engineering or related roles.
Strong hands-on experience with ETL/ELT development. Advanced SQL skills.
Strong experience with AWS cloud services.
Hands-on experience with Apache Spark / PySpark. S
trong experience working with AWS EMR.
Experience with AWS S3, Glue, and Redshift.
Strong programming experience in Python or Scala.
Experience working with large datasets and distributed data processing.
Understanding of data warehousing and data modelling concepts.