You have strong hands-on technical skills and experience in data engineering, with a track record of building and maintaining scalable data systems and pipelines. You excel at solving data engineering challenges and contributing to innovative solutions
Experience developing and optimizing data workflows, applying business logic for data enrichment, and addressing technical challenges with creative solutions
Strong knowledge of building and scaling data infrastructure, including integration with core platforms
Experience working with data quality challenges and implementing validation mechanisms
Self-motivated with the ability to manage tasks and collaborate effectively within a team
Ability to align work with broader organizational goals and contribute to strategic initiatives
Proactively identifies potential risks and helps implement solutions early in the project lifecycle
Eager to learn, grow, and contribute to a collaborative, high-performing engineering team
4- 6 years of experience in data engineering, specializing in building scalable data pipelines and enrichment processes, with a track record of working with large datasets, including ingestion, transformation, and optimization
Proficiency in Spark, Python, and SQL for building scalable data processing pipelines
Hands-on experience with Kubernetes for container orchestration and deployment
Hands - on experience with Elasticsearch
Strong background in AWS, including services such as S3, Lambda, ECS, and RDS for data infrastructure
Experience with AWS EMR and Databricks to optimize large-scale data workflows
Not meeting all the requirements but still feel like you’d be a great fit? Tell us how you can contribute to our team in a cover letter!