Middle/Senior Data Engineer (#4043)

N-iX is looking for a Middle/Senior Data Engineer who would be involved in designing, implementing, and managing the new Data Lakehouse for our customer in the e-commerce domain. The ideal candidate has worked with data-related services in AWS, Snowflake, and experience in modern data approaches.   

Our Client is a global full-service e-commerce and subscription billing platform on a mission to simplify software sales everywhere. For nearly two decades, we’ve helped SaaS, digital goods, and subscription-based businesses grow by managing payments, global tax compliance, fraud prevention, and recurring revenue at scale. Our flexible, cloud-based platform, combined with consultative services, helps clients accelerate growth, reach new markets, and build long-term customer relationships.

Data is at the heart of everything we do — powering insights, driving innovation, and shaping business decisions. We are building a next-generation data platform, and we’re looking for a Senior Data Engineer to help us make it happen.

As a Data Engineer, you will play a key role in designing and building our new Data Lakehouse on AWS, enabling scalable, reliable, and high-quality data solutions. You will work closely with senior engineers, data architects, and product managers to create robust data pipelines, develop data products, and optimize storage solutions that support business-critical analytics and decision-making.

Responsibilities:

• Build and operate a modern Data Lakehouse on AWS (S3 + Iceberg) supporting ingestion, storage, transformation, and serving layers.
• Design and optimize ETL pipelines using PySpark, Airflow (MWAA), and Snowflake for scalability and cost efficiency.
• Automate workflows with Python scripts, integration validation, and monitoring across sources and layers.
• Implement and enforce data quality controls (Glue Data Quality, Great Expectations) and contribute to governance best practices.
• Collaborate with cross-functional teams (Data and Software Architects, Engineering Managers, Product Owners, and Data/Power BI Engineers) to refine data requirements and deliver trusted and actionable insights.
• Support CI/CD practices via GitLab, ensuring version-controlled, testable, and auditable data processes.
• Document data flows and business logic to maintain transparency, lineage, and knowledge transfer across teams.
• Continuously improve operational efficiency by troubleshooting issues, monitoring performance, and suggesting technical enhancements.
  
  

Requirements:

• 3+ years of hands-on experience in Data Engineering, preferably in lakehouse or hybrid architectures.
• Proficiency in PySpark for large-scale transformations across layered datasets.
• Experience with Airflow (MWAA) for orchestrating end-to-end pipelines, dependencies, and SLA-driven workloads.
• Knowledge of AWS services used in modern data platforms: S3 + Iceberg, Glue (Catalog + Data Quality), Athena, EMR.
• Experience in Snowflake for analytics serving and cross-platform ingestion.
• Proficiency in Python for automation, validation, and auxiliary data workflows.
• Understanding of data modeling principles and harmonization principles, including SCD handling and cross-source entity resolution.
• Familiarity with CI/CD pipelines in Git/GitLab, ensuring tested, version-controlled, and production-ready deployments.
• Experience working with BI ecosystems (e.g., Power BI, dbt-like transformations, semantic layers).
• Upper-Intermediate English or higher, with the ability to document and explain complex concepts.