Data Engineer - AWS Platform (5-7 yrs)

Job Summary :

We are looking for a skilled AWS Data Engineer to design, build, and maintain large-scale data systems on Amazon Web Services (AWS). The ideal candidate will have a strong background in data engineering, experience with AWS services, and a passion for delivering high-quality data solutions.

Responsibilities :

- Design, build, and maintain large-scale data systems on AWS

- Develop and implement data pipelines using AWS services such as S3, Glue, and Lambda

- Collaborate with data scientists and analysts to design and implement data models and architectures

- Ensure data quality, security, and compliance with regulatory requirements

- Optimize data systems for performance, scalability, and cost-effectiveness

- Stay up-to-date with the latest AWS services and features

- Collaborate with cross-functional teams to identify and prioritize project requirements

Requirements:

- 5+ years of experience in data engineering, preferably on AWS

- Strong understanding of data engineering principles, data modeling, and data architecture

- Experience with AWS services such as S3, Glue, Lambda, and Redshift

- Proficiency in programming languages such as Python, Java, or Scala

- Experience with data pipeline tools such as Apache Beam, Apache Spark, or AWS Glue

- Strong understanding of data security, compliance, and governance

- Excellent communication and collaboration skills

- Bachelor's degree in Computer Science, Engineering, or related field

Nice to Have :

- Experience with containerization using Docker

- Knowledge of machine learning or data science concepts

- Experience with data warehousing and business intelligence tools

- Certification in AWS services such as AWS Certified Data Engineer or AWS Certified Solutions Architect

- Experience with Agile development methodologies and version control systems

What We Offer :

- Competitive salary and benefits package

- Opportunity to work with a talented team of engineers

- Collaborative and dynamic work environment

- Professional development opportunities and training budget

- Flexible working hours and remote work options

- Access to cutting-edge technologies and tools