Design and implement scalable data pipelines to support our cutting-edge applications

Ensure data quality and data accuracy across all stages of data processing

Collaborate with cross-functional teams to understand business requirements and develop solutions that meet their needs

Develop and maintain codebase in accordance with industry best practices and standards

Troubleshoot and resolve issues in a timely and effective manner

Optimize data processing algorithms and improve application performance

Ensure compliance with data security and data privacy regulations

Conduct code reviews and ensure high code quality and compliance with standards and guidelines

Participate in architectural and technical discussions to help shape the product roadmap

Stay up-to-date with emerging trends and technologies in data engineering and analytics

At least 3+ years of experience as a Data Software Engineer or in similar roles

Expertise in one of the languages (Python, Spark, PySpark, SQL) for building scalable and high-performance applications

Experience with Microsoft Azure for cloud-based infrastructure and application management

Experience using Databricks for building robust data pipelines

Experience using Azure DevOps, GitHub, or other version control systems

Familiarity with developing end-to-end production solutions

Ability to tie loose ends together for solutions across systems

Excellent communication skills in spoken and written English, at an upper-intermediate level or higher

Experience with GCP and AWS cloud platforms

Experience with Apache Kafka and Apache Beam for building data pipelines

Experience with machine learning and data science tools and frameworks