Senior Data Engineer (Redshift)

About this role

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.

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.

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.

Candidate journey: ⭕️ Recruiter call ➔ ⭕️ Technical call with the hiring manager ➔ ⭕️ Meet the future stakeholders

Check out some of our products

Muscle Booster — https://musclebooster.fitness/ https://musclebooster.fitness/

Yoga-Go — https://yoga-go.io/ https://yoga-go.io/

WalkFit -http://walkfit.pro