Senior Backend / Data Engineer (Python/Django)

Addeptois a leading AI consulting () and data engineering () 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,Addeptohelps 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,Addeptohas 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 earnedAddeptorecognition by Forbes as one of the top 10 AI consulting companies worldwide.

As part of KMS Technology, a US-based global technology group,Addeptocombines 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 aSenior 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 ondata 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.
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.
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.
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 scalabledata ingestion pipelinesfor file-based and API data sources using Python.
Design and develop scalabledata ingestion pipelinesfor file-based and API data sources using Python.
* Build and maintain backend components responsible fordata processing, validation, and integration.
Build and maintain backend components responsible fordata processing, validation, and integration.
* Design and developREST APIs using Python and Django.
Design and developREST APIs using Python and Django.
* Implement robustdata quality, validation, and error-handling mechanisms.
Implement robustdata quality, validation, and error-handling mechanisms.
* Design and maintain data models and work with moderncloud data platforms and warehouses.
Design and maintain data models and work with moderncloud data platforms and warehouses.
* Develop and maintain automated data-quality tests.
Develop and maintain automated data-quality tests.
* Work withcloud servicesand workflow orchestration tools such as Airflow.
Work withcloud servicesand workflow orchestration tools such as Airflow.
* Contribute toCI/CD pipelinesand application environment configuration.
Contribute toCI/CD pipelinesand application environment configuration.
* Ensure solutions are reliable, maintainable, scalable, and production-ready.
Ensure solutions are reliable, maintainable, scalable, and production-ready.
* Write and maintain technical documentation and operational runbooks.
Write and maintain technic