Skip to content
Principal Software Engineer – Data
| Company | Veeam Software |
|---|
| Location | Waterbury, CT, USA |
|---|
| Salary | $215000 – $307100 |
|---|
| Type | Full-Time |
|---|
| Degrees | |
|---|
| Experience Level | Expert or higher |
|---|
Requirements
- 10+ years of experience as a software engineer, bulk of it in building and deploying production data pipelines at scale in the cloud (preferably AWS), using orchestration tools like Apache Airflow.
- Proven experience in designing and scaling highly-performant data pipelines leveraging AWS services such as S3, Athena, Lambda, and RDS.
- Fluency in a modern programming language relevant to data engineering (e.g., Python).
- Strong experience working with relational databases (e.g., PostgreSQL, MySQL, etc) and data warehousing solutions (e.g., AWS Athena).
- Experience in leading other engineers in designing and implementing solutions for building and managing data pipelines and data infrastructure.
Responsibilities
- Designing and implementing scalable ETL/ELT data pipelines handling large volumes of data to support global expansion of our patent-pending forensics products that have been used by thousands of customers.
- Driving the expansion and management of our data processing infrastructure across multiple AWS regions.
- Analyzing current data architecture for security, scalability, performance, and data quality, and implementing appropriate solutions.
- Developing and deploying serverless data processing solutions using AWS Lambda, orchestrated using Apache Airflow.
- Designing and optimizing data architecture within relational databases (e.g., AWS RDS) and data warehouses (e.g., AWS Athena).
- Collaboration with cross-functional teams, including the product manager, UX designer, and other engineers to understand data processing requirements and translate them into technical solutions.
- Writing clean, maintainable, and well-documented code following best practices and coding standards, with data quality and security top of mind.
- Implementing observability and alerting for data pipelines to proactively identify and resolve issues.
- Conducting code and data pipeline reviews, provide constructive feedback, and mentor peers to ensure data quality and continuous improvement.
Preferred Qualifications
- Experience running data pipelines in multiple cloud environments is highly desirable.
