Senior Backend / Data Engineer (Python/Django)

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 Senior Backend / Data Engineer (Python/Django), you will join a senior engineering team working on a greenfield data platform. You will be involved in building the solution end-to-end, combining strong backend engineering with data ingestion and data processing.

The project involves integrating data from multiple file-based and API sources into a modern cloud data warehouse, with a strong focus on data quality, reliability, scalability, and production readiness. We are also looking for talented engineers to join other exciting data projects, including:

• Development and maintenance of a large platform for processing automotive data. A significant amount of data is processed in both streaming and batch modes. The technology stack includes Spark, Cloudera, Airflow, Iceberg, Python, and AWS.

• 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.

• Centralized reporting platform for a growing US telecommunications company. This project involves implementing BigQuery and Looker as the central platform for data reporting. It focuses on centralizing data, integrating various CRMs, and building executive reporting solutions to support decision-making and business growth.

🚀 Your main responsibilities:

• Design and develop scalable data ingestion pipelines for file-based and API data sources using Python.

• Build and maintain backend components responsible for data processing, validation, and integration.

• Design and develop REST APIs using Python and Django.

• Implement robust data quality, validation, and error-handling mechanisms.

• Design and maintain data models and work with modern cloud data platforms and warehouses.

• Develop and maintain automated data-quality tests.

• Work with cloud services and workflow orchestration tools such as Airflow.

• Contribute to CI/CD pipelines and application environment configuration.

• Ensure solutions are reliable, maintainable, scalable, and production-ready.

• Write and maintain technical documentation and operational runbooks.

• Collaborate with engineers and stakeholders to translate business and technical requirements into effective solutions.

• Use AI-assisted development tools and workflows as part of day-to-day software delivery.

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

• At least 4 years of commercial experience in Backend Engineering, Data Engineering, or building production data-intensive systems.

• Strong programming skills in Python, including clean code and solid software engineering practices.

• Hands-on commercial experience with Django and building REST APIs.

• Experience designing and developing data ingestion / ETL or ELT pipelines from file-based and API sources.

• Experience with modern cloud data platforms or warehouses, such as Snowflake or Databricks.

• Working knowledge of at least one major cloud platform (AWS, Azure, or GCP).

• Experience with workflow orchestration tools such as Airflow or equivalent.

• Strong understanding of data validation, data quality, and error-handling design.

• Experience working with CI/CD and production environments.

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

• Experience using AI coding assistants or AI-supported development workflows.

• Excellent communication skills and the ability to clearly document technical decisions.

• Fluent English (at least C1 level).
  

🎁 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 development paths, knowledge-sharing initiatives, language classes, and sponsored training and conferences. Benefit from partnerships with Databricks and Anthropic, which provide access to industry-leading training materials and certification programs.

• 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.