Job Description

Job Title: AWS Data Engineer

Work Location: Irvine, CA (Day 1 Onsite - Hybrid)

Job Overview:

The Cloud Data Platforms team, part of the Insights and Data Global Practice, has experienced significant growth and success across multiple industries and projects. This team is comprised of Data Engineers, Platform Engineers, Solutions Architects, and Business Analysts, all dedicated to leading customers through digital and data transformation using modern cloud platforms. We specialize in leveraging the latest frameworks, reference architectures, and cutting-edge technologies, focusing on AWS, Azure, and Google Cloud.

Your Role:

We are seeking skilled AWS Data Engineers with a passion for cloud technologies. In this role, you will:

• Design and Develop Data Pipelines: Build scalable pipelines to ingest, process, and transform data, ensuring its readiness for analytics and reporting.
• Implement ETL/ELT Processes: Develop ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) workflow to seamlessly move data from various source systems into Data Warehouses, Data lakes, and lake houses, utilizing AWS tools and open-source technologies.
• Adopt DevOps Practices: Incorporate DevOps methodologies such as continuous integration and deployment, infrastructure as code, and automation to enhance data engineering efficiency and reliability.
• Design Data Solutions: Use your analytical expertise to design innovative data solutions that meet complex business needs and support data-driven decision-making.
   

Your Responsibilities:

• Extensive hands-on experience with AWS data services, including AWS EMR, Glue, S3, Redshift, and related technologies.
• Proven ability to architect and design advanced data engineering frameworks using AWS EMR/Glue, Apache Spark, and other AWS data technologies.
• Strong expertise in using DBT or similar frameworks and applying modern data architecture principles.
• Develop strategic plans for scalable data solutions, overseeing both implementation and ongoing maintenance.
• Define and enforce architectural standards and best practices for data ingestion, processing, storage, and retrieval systems.
• Lead collaboration across cross-functional teams to ensure data engineering frameworks are adopted and leveraged to deliver effective solutions.
• Provide mentorship and architectural guidance to data engineering teams to drive innovation and efficiency.
   

Minimum Qualification:

• Bachelor’s or Masters degree in Computer Science, Engineering, or a related technical field.
• 7+ years of experience in data engineering with a strong focus on AWS-based solutions.
• Proficient in designing and implementing data engineering frameworks such as DBT, SQLMesh, or Coalesce.
• Extensive knowledge of AWS services, particularly AWS EMR and Glue.
• Strong understanding of data warehousing, ETL processes, and data modeling techniques.
   

Preferred Qualifications:

• AWS-certified solutions architect or AWS-certified data engineer certification.
• Experience with infrastructure as code tools such as Terraform or AWS cloud formation.
• Your Skills and Experience:
• AWS tools expertise: Hands-on experience with AWS Lambda, Amazon Kinesis, Amazon EMR, Amazon Athena, Amazon DynamoDB, Amazon CloudWatch, Amazon SNS, and AWS Step Functions.
• Programming Skills: Strong proficiency in modern programming languages like Python, Java, and Scala.
• Data Storage Technologies: Extensive knowledge of data warehouse technologies and big data ecosystems, including AWS Redshift, AWS RDS, and Hadoop.
• AWS Data Lakes Experience: Proven track record of working with AWS data lakes on AWS S3 to manage and process both structured and unstructured data.
• Good working knowledge of AWS Tech stack S3, building data pipelines, and data Ingestion.
• Proficient in querying databases for data analysis and understanding codePerson should be able to do data analysis independently.