Senior Data Engineer (Redshift)

Headquarters: Cyprus URL: http://welltech.com Who Are We? Welltech is a global wellness technology company with Ukrainian roots. Our mission is to build and scale wellness apps globally through state-of-the-art, tech-driven performance marketing.

We are one of the most established players in the wellness app space, and we are accelerating. Over 25.5 million people across the world use our apps — Muscle Booster, Yoga-Go, and WalkFit — to build healthier habits, move more, and feel better every day. Every subscription represents a real person making a real change in their life, and we take that seriously.

With 500+ people across hubs in Cyprus, Ukraine, Poland, Spain, and the UK , we combine the scale of a market leader and the drive of a team that's just getting started. What We're Looking For As a Senior Data Engineer , you will play a crucial role in building and maintaining the foundation of our data ecosystem. You’ll work alongside data engineers, analysts, and product teams to create robust, scalable, and high-performance data pipelines and models.

Your work will directly impact how we deliver insights, power product features, and enable data-driven decision-making across the company. This role is perfect for someone who combines deep technical skills with a proactive mindset and thrives on solving complex data challenges in a collaborative environment. Challenges You’ll Meet: Pipeline Development and Optimization: Build and maintain reliable, scalable ETL/ELT pipelines using modern tools and best practices, ensuring efficient data flow for analytics and insights.

Data Modeling and Transformation: Design and implement effective data models that support business needs, enabling high-quality reporting and downstream analytics. Collaboration Across Teams: Work closely with data analysts, product managers, and other engineers to understand data

and deliver solutions that meet the needs of the business. Ensuring Data Quality: Develop and apply data quality checks, validation frameworks, and monitoring to ensure the consistency, accuracy, and reliability of data. Performance and Efficiency: Identify and address performance issues in pipelines, queries, and data storage.

Suggest and implement optimizations that enhance speed and reliability. Security and Compliance: Follow data security best practices and ensure pipelines are built to meet data privacy and compliance standards. Innovation and Continuous Improvement: Test new tools and approaches by building Proof of Concepts (PoCs) and conducting performance benchmarks to find the best solutions.

Automation and CI/CD Practices: Contribute to the development of robust CI/CD pipelines (GitLab CI or similar) for data workflows, supporting automated testing and deployment.