Data Engineer • Mid-Level

Who you are

You have at least 4 years of experience in data engineering, demonstrating ownership of complex data systems and a solid understanding of data mesh principles and decentralized data architecture. Your technical background includes a Bachelor's degree in a relevant field such as Computer Science or Mathematics, equipping you with the skills necessary to tackle challenging data problems.

You possess strong expertise in AWS data lake technologies, including S3, Glue, Lake Formation, Athena, and Redshift. Your experience with ETL/ELT pipelines using AWS Glue and PySpark allows you to ensure scalable, high-performance data processing across platforms. You are also familiar with GraphQL APIs, which you will use to expose domain-owned data products.

Your collaborative spirit shines through as you work closely with product, engineering, and analytics teams to deliver robust, reusable data solutions. You are committed to supporting data governance, quality, observability, and API design best practices, ensuring that the data infrastructure is reliable and efficient.

You stay current with emerging technologies and industry trends, continuously seeking ways to evolve the data platform. Your ability to contribute to automation and CI/CD practices for data infrastructure and pipelines is a testament to your proactive approach in the field.

Desirable

Experience with near real-time analytics and reporting is a plus, as is familiarity with data governance frameworks. You are encouraged to apply even if your experience doesn't match every requirement, as your curiosity and willingness to learn are highly valued.

What you'll do

In this role, you will design and build domain-oriented data products that support near real-time reporting. You will contribute to the design and implementation of a data mesh architecture, ensuring that data products are easily accessible and manageable. Your responsibilities will include building and maintaining a modern AWS-based data lake, utilizing services such as S3, Glue, Lake Formation, Athena, and Redshift to create a robust data environment.

You will develop and optimize ETL/ELT pipelines using AWS Glue and PySpark, supporting both batch and streaming data workloads. Implementing AWS DMS pipelines to replicate data into Aurora PostgreSQL for near real-time analytics will be a key part of your role, allowing for timely insights and reporting.

Collaboration is essential, as you will work with various teams to deliver data solutions that meet business needs. You will also support data governance initiatives, ensuring that data quality and observability are prioritized in all projects. Your contributions to automation and CI/CD practices will help streamline data infrastructure and enhance overall efficiency.

What we offer

Suvoda provides a dynamic work environment where innovation is encouraged. You will have the opportunity to work with cutting-edge technologies and contribute to the evolution of our data platform. We value your expertise and are committed to supporting your professional growth through continuous learning opportunities and collaboration with talented colleagues.

Join us in shaping the future of data engineering at Suvoda, where your skills will make a significant impact on our data-driven initiatives. We look forward to welcoming you to our team.