Must have

• Boost

• Data pipelines

• ETL

• Data modeling

• Storage

• Security

• CI/CD Pipelines

• GitLab CI

• Automated testing

• Data engineering

• AWS

• Redshift

• AWS S3

• Amazon RDS

• Glue

• AWS Lambda

• Kinesis

• AWS Redshift

• Amazon SQS

• MWAA

• Python

• SQL

• Airflow

• dbt

• GitLab

• Datadog

• Grafana

• Graylog

• REST API

• OAuth

• English (C1)

Nice to have

• Terraform

• Amazon EMR

• Amazon EKS

• Athena

• AWS EC2

• Data warehouses

• Snowflake

• PySpark

• Big Data

Requirements description

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.

You Should Have:

• 4+ years of experience in data engineering or backend development, with a strong focus on building production-grade data pipelines.
• Solid experience working with AWS services ( Redshift, 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.

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.

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

Offer description

🚀 Who Are We?

Welcome to Welltech—where health meets innovation! 🌍 As a global leader in Health & Fitness industry, we’ve crossed over 200 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.

✨ 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!

Your responsibilities

1. 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.
2. Data Modeling and Transformation: Design and implement effective data models that support business needs, enabling high-quality reporting and downstream analytics.
3. 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.
4. Ensuring Data Quality: Develop and apply data quality checks, validation frameworks, and monitoring to ensure the consistency, accuracy, and reliability of data.
5. Performance and Efficiency: Identify and address performance issues in pipelines, queries, and data storage. Suggest and implement optimizations that enhance speed and reliability.
6. Security and Compliance: Follow data security best practices and ensure pipelines are built to meet data privacy and compliance standards.

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