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Senior Data Engineer

icon building Company : Zartis
icon briefcase Job Type : Full Time
icon remote-alt Remote / Work from Home

Job Description - Senior Data Engineer


Senior Data Engineer


The company and our mission: 


Zartis is a global AI transformation and technology consulting partner where talented engineers and technologists work on cutting edge innovation. We partner with ambitious organizations to design, build, and scale technology solutions that deliver real impact.


Our teams bring deep expertise in AI driven platforms, secure API architectures, and cloud native engineering. You will work on meaningful projects that accelerate the adoption of advanced technologies, from strategy and discovery through to full product delivery, helping turn complex challenges into measurable outcomes.


With engineering hubs across EMEA and LATAM, and long term partnerships in financial services, healthcare and life sciences, and energy and climate, we offer opportunities to work on projects that truly matter. Here, you will not just build technology, you will drive business impact and grow your career alongside industry leaders.


We are looking for a Senior Data Engineer to work on a project in the logistics 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 is at an exciting stage of its data journey. They are moving beyond the limitations of traditional business intelligence tooling and investing in a modern data platform that will become the foundation for analytics, reporting, machine learning, and customer-facing insights.


This is an opportunity to shape the company's data architecture from the ground up. Rather than maintaining an existing platform, you will help define how operational data is collected, transformed, and modeled to support both internal decision-making and future product capabilities.


The team is exploring Databricks as the foundation of its modern data platform and is looking for someone who enjoys solving complex data challenges while working closely with business stakeholders to understand what data should be captured and why.


What you will do:




  • Design, build, and maintain scalable data pipelines to ingest, transform, and process operational data.




  • Develop modern ETL/ELT workflows that deliver reliable, high-quality datasets.




  • Help design a scalable data warehouse/lakehouse architecture using modern cloud technologies.




  • Work closely with business stakeholders to understand reporting and analytics requirements.




  • Improve data quality, consistency, governance, and documentation across the platform.




  • Identify gaps in existing data collection and recommend improvements to tracking and data models.




  • Enable self-service analytics by delivering clean, well-structured datasets for downstream BI tools.




  • Prepare data models that support advanced analytics, machine learning, and customer-facing insights.




  • Contribute to establishing data engineering best practices, standards, and scalable architecture.




What you will bring:




  • Strong commercial experience in Data Engineering.




  • Proven experience designing and building modern data pipelines and ETL/ELT solutions.




  • Experience working with data warehouses or modern lakehouse architectures.




  • Strong SQL skills and experience modeling large datasets.




  • Experience with cloud-based data platforms, ideally Databricks.




  • Experience building or evolving data platforms from the ground up.




  • Strong understanding of data modeling, data quality, governance, and data architecture best practices.




  • Ability to work directly with business stakeholders to translate business problems into scalable data solutions.




  • Experience enabling Business Intelligence through clean, well-structured, analytics-ready datasets.




  • Experience preparing data for advanced analytics and machine learning use cases.




  • Strong analytical mindset with the ability to identify opportunities through data and recommend improvements to data collection.




  • Excellent communication skills, with a proactive and collaborative approach to problem solving.




Nice to have:




  • Experience with BI tools such as Power BI, Tableau, or Looker.




  • Experience designing customer-facing analytics or embedded reporting solutions.




  • Experience working in fast-growing product or technology companies.




What we offer: 




  • 100% Remote Work




  • WFH allowance: Monthly payment as financial support for remote working.




  • Career Growth: We have established a career development program accessible for all employees with a 360º feedback that will help us to guide you in your career progression.




  • Training: For Tech training at Zartis, you have time allocated during the week at your disposal. You can request from a variety of options, such as online courses (from Pluralsight and Educative.io, for example), English classes, books, conferences, and events.




  • Mentoring Program: You can become a mentor in Zartis or you can receive mentorship, or both.




  • Zartis Wellbeing Hub (Kara Connect): A platform that provides sessions with a range of specialists, including mental health professionals, nutritionists, physiotherapists, fitness coaches, and webinars with such professionals as well.




  • Multicultural working environment: We organize tech events, webinars, parties, and activities to do online team-building games and contests.




We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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