Data Engineer

5 days ago

Remote Warszawa, Czech Republic Welltech Full time

What We're Looking For

As a Data Engineer, you’ll work on building and supporting the data infrastructure that powers our internal analytics, reporting, and customer-facing products. You’ll develop reliable, well-structured data pipelines, collaborate with stakeholders to understand data requirements, and contribute to our data platform’s scalability and quality.

This role is ideal for someone with a few years of hands-on experience in data engineering who is ready to take the next step in a collaborative and growth-oriented team.

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
  • Monitoring: Datadog, Grafana, Graylog
  • Event validation process: Iglu schema registry

Required skills:

  • 2–3+ years of experience in data engineering, backend development, or similar technical roles.
  • Practical experience with AWS services, especially Redshift, S3, and Glue. Familiarity with Lambda, RDS, and Kinesis is a plus.
  • Solid skills in Python and SQL for data extraction, transformation, and scripting.
  • Familiarity with dbt for data transformation and documentation (or strong interest in learning it).
  • Exposure to streaming or micro-batching concepts and tools.
  • Understanding of CI/CD workflows, ideally using GitLab CI.
  • Willingness to work with event schema validation tools (e.g., Iglu, Schema Registry).
  • Strong communication and collaboration skills.
  • Experience working with APIs and integrations (REST, OAuth, webhook ingestion) or eagerness to build those skills.
  • Detail-oriented with a focus on producing clean, reliable, and maintainable data pipelines.
  • A proactive, curious mindset with a desire to continuously learn and grow.

Nice to Have:

  • Experience with Snowflake or other cloud DWH technologies.
  • Familiarity with event collection tools (e.g., Snowplow, Rudderstack).
  • Hands-on with PySpark for distributed processing.
  • Exposure to infrastructure as code (e.g., Terraform).
  • Interest in real-time data, customer data platforms (CDPs)

🚀 Who Are We?

Welcome to Welltech—where health meets innovation 🌍 As a global leader in Health & Fitness industry, we’ve crossed over 220 million installs with three life-changing apps, all designed to boost well-being for millions. Our mission? To transform lives through intuitive nutrition trackers, powerful fitness solutions, and personalized wellness journeys—all powered by a diverse team of over 700+ passionate professionals with presence across 5 hubs.

Why Welltech? Imagine joining a team where your impact on global health and wellness is felt daily. At Welltech, we strive to be proactive wellness partners for our users, while continually evolving ourselves.

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

✨ Why You’ll Love Being Part of Welltech:

  • Grow Together: Join a culture that champions both personal and professional growth. Here, you’ll thrive as we learn, evolve, and succeed together. 
  • Lead by Example: No matter your role, your leadership matters. Every team member is empowered to inspire and make an impact. 
  • Results-Driven: We’re all about achieving meaningful outcomes. It’s not just about the effort, but the difference we make every day. 
  • We Are Well-Makers: Be part of a movement that’s creating a healthier, happier world. Together, we make well-being a reality 
,[ Pipeline Development: Build and maintain ETL/ELT workflows using modern data tools and cloud services to ensure accurate, timely, and accessible data. , Data Modeling & Transformation: Implement and maintain data models for analytics use cases, working closely with senior engineers and analysts. , Team Collaboration: Collaborate with data analysts, product teams, and fellow engineers to gather requirements and support data delivery. , Data Quality & Validation: Apply basic data validation checks and contribute to maintaining high data quality across pipelines. , Monitoring & Maintenance: Monitor pipeline health and troubleshoot operational issues in collaboration with more senior engineers. , Process Automation: Contribute to scripting and automation of data workflows using Python and SQL, improving reliability and reducing manual work. , CI/CD & Deployment Support: Work with GitLab CI pipelines for data deployments, gradually building expertise in automated testing and deployment practices. , Learning & Growth: Learn and apply best practices in data engineering, guided by senior team members and peer reviews. ] Requirements: Boost, Data pipelines, Data engineering, ETL, Cloud, Data modeling, Data models, Use cases, Python, SQL, GitLab CI, Automated testing, AWS, Redshift, AWS S3, Glue, AWS Lambda, Amazon RDS, dbt, REST API, OAuth, AWS Redshift, Kinesis, Amazon SQS, MWAA, Airflow, GitLab, Datadog, Grafana, Graylog, Snowflake, DWH, PySpark, Infrastructure as Code, Terraform Additionally: Sport subscription, Private healthcare, International projects, Training budget, Lunch card.

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