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 requirements 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.
The company offers a role within a global wellness technology company with a mission to scale apps globally. You will work in a collaborative environment with a team of 500+ people, utilizing a modern tech stack including AWS, Python, SQL, dbt, and Airflow. The role provides opportunities for innovation, building Proof of Concepts, and working on high-impact data products like Muscle Booster, Yoga-Go, and WalkFit.
Required skills:
- 4+ years of experience in data engineering or backend development, with a strong focus on building production-grade data pipelines.
- 2-3+ years of experience working with AWS services (Administration of Redshift is a must).
- Solid experience working with AWS services (Spectrum, S3, RDS, Glue, Lambda, Kinesis, SQS).
- Proficient in Python and SQL for data transformation and automation.
- Experience with dbt for data modeling and transformation.
- Good understanding of streaming architectures and micro-batching for real-time data needs.
- Experience with CI/CD pipelines for data workflows (preferably GitLab CI).
- Familiarity with event schema validation tools/ solutions (Snowplow, Schema Registry).
- Excellent communication and collaboration skills.
- Strong problem-solving skills—able to dig into data issues, propose solutions, and deliver clean, reliable outcomes.
- A growth mindset—enthusiastic about learning new tools, sharing knowledge, and improving team practices.
Bonus Points / Nice to Have:
- Experience with additional AWS services: EMR, EKS, Athena, EC2.
- Hands-on knowledge of alternative data warehouses like Snowflake or others.
- Experience with PySpark for big data processing.
- Familiarity with event data collection tools (Snowplow, Rudderstack, etc.).
- Interest in or exposure to customer data platforms (CDPs) and real-time data workflows.
