Junior Data Engineer (Databricks)

Addepto is a leading AI consulting (https://addepto.com/ai-consulting/) and data engineering (https://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.

As a Junior Data Engineer, you will have the exciting opportunity to work with a team of technology experts on challenging projects across various industries, leveraging cutting-edge technologies. Here are some of the projects we are seeking talented individuals to join:

• Design and development of a universal data platform for global aerospace companies. This Azure and Databricks powered initiative combines diverse enterprise and public data sources. The data platform is at the early stages of the development, covering design of architecture and processes as well as giving freedom for technology selection.

• Data Platform Transformation for energy management association body. This project addressed critical data management challenges, boosting user adoption, performance, and data integrity. The team is implementing a comprehensive data catalog, leveraging Databricks and Apache Spark/PySpark, for simplified data access and governance. Secure integration solutions and enhanced data quality monitoring, utilizing Delta Live Table tests, established trust in the platform. The intermediate result is a user-friendly, secure, and data-driven platform, serving as a basis for further development of ML components.

• Design of the data transformation and following data ops pipelines for global car manufacturer. This project aims to build a data processing system for both real-time streaming and batch data. We’ll handle data for business uses like process monitoring, analysis, and reporting, while also exploring LLMs for chatbots and data analysis. Key tasks include data cleaning, normalization, and optimizing the data model for performance and accuracy.

🚀 Your main responsibilities: 

• Design scalable data processing pipelines for streaming and batch processing using Big Data technologies like Databricks, Airflow and/or Dagster.

• Contribute to the development of CI/CD and MLOps processes.

• Develop applications to aggregate, process, and analyze data from diverse sources.

• Collaborate with the Data Science team on Machine Learning projects, including text/image analysis and predictive model building.

• Develop and organize data transformations using Databricks/DBT and Apache Airflow.

• Translate business requirements into technical solutions and ensure optimal performance and quality.

🎯 What you’ll need to succeed in this role:

• At least 1 year of proven commercial experience developing, or maintaining Big Data systems.

• Hands-on experience with Big Data technologies, including Databricks, Apache Spark, Airflow, and DBT.

• Strong programming skills in Python: writing a clean code, OOP design.

• Experience in designing and implementing data governance and data management processes.

• Experience implementing and deploying solutions in cloud environments (with a preference for Azure).

• Practical knowledge of DevOps practices, including designing and maintaining CI/CD pipelines for data and ML workflows, and Terraform for Infrastructure as Code.

• Knowledge of how to build and deploy Power BI reports and dashboards for data visualization.

• Excellent understanding of dimensional data and data modeling techniques.

• Excellent communication skills and consulting experience with direct interaction with clients.

• Ability to work independently and take ownership of project deliverables.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Physics, or a related field.

🎁 Discover our perks & benefits:

• Work in a supportive team of passionate enthusiasts of AI & Big Data.

• Engage with top-tier global enterprises and cutting-edge startups on international projects.

• Enjoy flexible work arrangements, allowing you to work remotely or from modern offices and coworking spaces. 

• Accelerate your professional growth through career paths, knowledge-sharing initiatives, language classes, and sponsored training or conferences, including a partnership with Databricks, which offers industry-leading training materials and certifications.

• Choose your preferred form of cooperation - B2B or a contract of mandate - and enjoy 20 fully paid days off

• Participate in team-building events and utilize the integration budget.

• Celebrate work anniversaries, birthdays, and milestones.

• Access medical and sports packages, eye care, and well-being support services, including psychotherapy and coaching.

• Get full work equipment for optimal productivity, including a laptop and other necessary devices.

• With our backing, you can boost your personal brand by speaking at conferences, writing for our blog, or participating in meetups.

• Experience a smooth onboarding with a dedicated buddy, and start your journey in our friendly, supportive, and autonomous culture.

Are you interested in Addepto and would like to join us?

Get in touch! We are looking forward to receiving your application. Would you like to know more about us?

Visit our website (career page) and social media (Facebook, LinkedIn, Instagram).