Addepto is a leading AI consulting (addepto.com/ai-consulting/) and data engineering (addepto.com/data-engineering-services/) company that builds scalable, ROI-focused AI solutions for some of the world's largest enterprises and pioneering startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. With an exclusive focus on Artificial Intelligence and Big Data, Addepto helps organizations unlock the full potential of their data through systems designed for measurable business impact and long-term growth.
The company's work extends beyond client engagements. Drawing from real-world challenges and insights, Addepto has developed its own product - ContextClue - and actively contributes open-source solutions to the AI community. This commitment to transforming practical experience into scalable innovation has earned Addepto recognition by Forbes as one of the top 10 AI consulting companies worldwide.
As part of KMS Technology, a US-based global technology group, Addepto combines deep AI specialization with enterprise-scale delivery capabilities—enabling the partnership to move clients from AI experimentation to production impact, securely and at scale.
We are looking for an experienced Data Engineer with strong skills in GCP, Snowflake, dbt, Python, SQL, and Data Analytics to join our team. You will work on international data engineering and analytics projects, focusing on building scalable data solutions, modernizing data warehouses, and supporting data-driven business decisions.
Project areas include:
- Data Warehouse & BI Modernization – refactoring data models and supporting migrations between BI platforms (e.g., Looker to Omni).
- CRM Data Integration – developing and optimizing data models to support CRM migrations and integrations (e.g., HubSpot).
- Commercial & Growth Analytics – building analytical solutions for customer acquisition, retention, churn, revenue, and business performance.
- Data Quality & Self-Service Analytics – improving data reliability, implementing semantic layers, and enabling accessible analytics and AI-ready datasets.
Discover our perks and benefits:
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Work in a supportive team of passionate enthusiasts of AI & Big Data.
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Engage with top-tier global enterprises and cutting-edge startups on international projects.
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Enjoy flexible work arrangements, allowing you to work remotely or from modern offices and coworking spaces.
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Accelerate your professional growth through career paths, knowledge-sharing initiatives, language classes, and sponsored training or conferences, including partnerships with Databricks and Anthropic, which offer industry-leading training materials and certifications.
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Participate in team-building events and utilize the integration budget.
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Celebrate work anniversaries, birthdays, and milestones.
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Access medical and sports packages, eye care, and well-being support services, including psychotherapy and coaching.
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Get full work equipment for optimal productivity, including a laptop and other necessary devices.
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With our backing, you can boost your personal brand by speaking at conferences, writing for our blog, or participating in meetups.
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Experience a smooth onboarding with a dedicated buddy, and start your journey in our friendly, supportive, and autonomous culture.
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Design, develop, and optimize data pipelines and data models using modern cloud technologies.
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Build and maintain dbt models and complex data transformations using Python and SQL.
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Support data warehouse modernization, BI migrations, and integration of multiple data sources.
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Develop analytical datasets and reporting solutions to support business decisions.
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Ensure data quality, testing, monitoring, and documentation.
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Collaborate with engineering teams, analysts, and business stakeholders to deliver scalable data solutions.
What you’ll need to succeed in this role:
- 3+ years of commercial experience in Data Engineering or Analytics Engineering.
- Strong hands-on experience with GCP (BigQuery) and Snowflake.
- Advanced proficiency in Python and SQL, including complex data transformations, data processing, and query optimization.
- Strong practical experience with dbt, including developing, testing, and optimizing data models.
- Solid understanding of data warehousing, data modelling, ETL/ELT processes, and data architecture best practices.
- Hands-on experience with BI and reporting tools, such as Looker, LookML, Omni, Power BI, or Tableau.
- Experience with workflow orchestration tools, such as Apache Airflow or equivalent solutions.
- Experience with Git, CI/CD pipelines, code reviews, and automated testing.
- Good understanding of data quality, monitoring, and data governance practices.
- Strong analytical and problem-solving skills, with the ability to work independently and collaborate with business stakeholders.
- Excellent English communication skills (C1 minimum).
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