Senior Data Engineer

The company and our mission :

Zartis is a digital solutions provider working across technology strategy, software engineering and product development.

We partner with firms across financial services, MedTech, media, logistics technology, renewable energy, EdTech, e-commerce, and more. Our engineering hubs in EMEA and LATAM are full of talented professionals delivering business success and digital improvement across application development, software architecture, CI / CD, business intelligence, QA automation, and new technology integrations.

We are looking for a Data Engineer to work on a project in the Technology industry.

The project :

Our teammates are talented people that come from a variety of backgrounds. We’re committed to building an inclusive culture based on trust and innovation.

You will be part of a distributed team developing new technologies to solve real business problems. Our client empowers organizations to make smarter, faster decisions through the seamless integration of strategy, technology, and analytics. They have helped leading brands harness their marketing, advertising, and customer experience data to unlock insights, enhance performance, and drive digital transformation.

We are looking for someone with good communication skills, ideally with experience making decisions, being proactive, used to building software from scratch, and with good attention to detail.

What you will do :

• Designing performant data pipelines for the ingestion and transformation of complex datasets into usable data products.
• Building scalable infrastructure to support hourly, daily, and weekly update cycles.
• Implementing automated QA checks and monitoring systems to catch data anomalies before they reach clients.
• Re-architecting system components to improve performance or reduce costs.
• Supporting team members through code reviews and collaborative development.
• Building enterprise-grade batch and real-time data processing pipelines on AWS, with a focus on serverless architectures.
• Designing and implementing automated ELT processes to integrate disparate datasets.
• Collaborating across multiple teams to ingest, extract, and process data using Python, R, Zsh, SQL, REST, and GraphQL APIs.
• Transforming clickstream and CRM data into meaningful metrics and segments for visualization.
• Creating automated acceptance, QA, and reliability checks to ensure business logic and data integrity.
• Designing appropriately normalized schemas and making informed decisions between SQL and NoSQL solutions.
• Optimizing infrastructure and schema design for performance, scalability, and cost efficiency.
• Defining and maintaining CI / CD and deployment pipelines for data infrastructure.
• Containerizing and deploying solutions using Docker and AWS ECS.
• Proactively identifying and resolving data discrepancies, and implementing safeguards to prevent recurrence.
• Contributing to documentation, onboarding materials, and cross-team enablement efforts.

What you will bring :

Nice to have :

What we offer :