Veltris - Senior Data Engineer

Senior Data Engineer

Position Overview :

We are seeking an experienced Senior Data Engineer to join our growing data team. The ideal candidate will have extensive experience building and maintaining scalable data infrastructure on AWS, with a proven track record of designing robust data pipelines and systems that support business-critical analytics and machine learning initiatives.

Key Responsibilities :

Data Infrastructure & Architecture :

- Architect and implement data warehouses, data lakes, and real-time streaming solutions

- Optimize data storage, processing, and retrieval systems for performance and cost efficiency

- Ensure data quality, consistency, and reliability across all data systems

- Leverage AWS services including S3, Redshift, EMR, Glue, Lambda, Kinesis, and RDS

- Implement Infrastructure as Code (IaC) using tools like CloudFormation or Terraform

- Monitor and optimize cloud resource utilization and costs

- Ensure security best practices and compliance standards are met.

Data Engineering & Development :

- Develop and maintain complex data transformations using SQL, Java/Python, and/or Scala

- Build automated data validation and monitoring systems

- Create and maintain comprehensive documentation for data systems and processes

- Collaborate with data scientists and analysts to understand requirements and deliver solutions.

Leadership & Collaboration :

- Work closely with cross-functional teams including product, engineering, and business stakeholders

- Participate in architectural decisions and technical reviews

- Drive best practices for data engineering within the organization.

Required Qualifications :

Technical Skills :

- 8+ years of experience in data engineering or related field

- Strong expertise in AWS data services and cloud architecture

- Proficiency in Python and SQL for data processing and analysis

- Experience with big data technologies such as Spark, Hadoop, or similar frameworks

- Knowledge of data modeling techniques and database design principles

- Experience with version control systems (Git) and CI/CD pipelines

Data Engineering Expertise :

- Proven experience building and maintaining large-scale data pipelines

- Strong understanding of data warehousing concepts and dimensional modeling

- Experience with real-time data processing and streaming technologies

- Knowledge of data governance and data quality frameworks

- Familiarity with containerization technologies (Docker, Kubernetes)

AI & Productivity Tools :

- Experience using AI tools to enhance development productivity

- Demonstrated ability to integrate AI-powered solutions into data workflows

- Understanding of how AI tools can optimize data engineering processes and code quality