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.We offer*:
Flexible working format - remote, office-based or flexible A competitive salary and good compensation package Personalized career growth Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) Active tech communities with regular knowledge sharing Education reimbursement Memorable anniversary presents Corporate events and team buildings Other location-specific benefits*not applicable for freelancers