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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.

Tech Stack You’ll Work With:

  • Cloud: AWS (Redshift, Spectrum, S3, RDS, Lambda, Kinesis, SQS, Glue, MWAA)
  • Languages: Python, SQL
  • Orchestration: Airflow (MWAA)
  • Modeling: dbt
  • CI/CD: GitLab CI (including GitLab administration)
  • Monitoring: Datadog, Grafana, Graylog
  • Event validation process: Iglu schema registry
  • APIs & Integrations: REST, OAuth, webhook ingestion
  • Infra-as-code (optional): Terraform

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.

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.

Welltech

Welltech

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