About the job
Join Qodea, a leading global technology group headquartered in London, where we harness the power of advanced technology, including artificial intelligence, to empower organizations in navigating transformative changes.
With a team of over 600 experts across Europe, North America, and Asia, and supported by Marlin Equity Partners, we are committed to delivering innovative solutions that drive business success.
Our mission is to help clients:
- Work Smarter: Build modern, scalable infrastructures, applications, and workflows that enhance profitability.
- Engage Personally: Craft digital experiences that attract attention, boost sales, and foster customer loyalty.
- Stay Secure: Develop security, governance, and compliance frameworks that protect against threats and operational disruptions.
We collaborate with some of the world's most recognized brands, tackling challenges in various sectors from highly regulated financial institutions to dynamic tech startups and global retail giants. Our approach is consistent: we swiftly deliver practical solutions and work alongside clients to sustain and optimize these solutions over the long term while enhancing their teams’ capabilities.
Your Impact:
As a Machine Learning and Data Engineer, you will play a critical role in shaping the intelligence layer of our clients' digital ecosystems. This position is ideal for innovative thinkers who excel in solving complex problems and are dedicated to achieving measurable results with integrity. Your responsibilities will include transforming raw data into actionable insights through the design and implementation of robust data pipelines and sophisticated machine learning models.
Key Responsibilities:
- Design and deploy scalable data pipelines and production-grade ML models using Python and SQL to address high-stakes business challenges.
- Execute data modeling practices, including Schema design, Data Vault, and Kimball techniques, to ensure the delivery of high-quality and actionable data environments.
- Oversee the complete MLOps lifecycle, from data wrangling and experimentation to deployment and monitoring, utilizing Vertex AI and dbt.
- Collaborate with global clients to translate complex data insights and AI solutions into measurable business outcomes.
- Implement large-scale data processing frameworks like Apache Beam, Spark, or Flink for both batch and streaming data.
- Maintain a consultative approach focused on resolving clients' most challenging technical issues.
- Adopt a methodical and proactive stance towards technical experimentation, applying storytelling skills to convey technical complexities to non-technical stakeholders.

