Senior Data Engineer (Spark)

Important: Addepto may publish job opportunities on external job boards, but all applications are collected and processed through our official recruitment system.

Please make sure that any further recruitment communication you receive comes from an official Addepto recruitment channel. If you receive a job offer, interview invitation, or recruitment email from an unofficial or unverified source, please be cautious, as it may not come from Addepto.

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 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:

• 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.

🎁 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 and Anthropic, which offers industry-leading training materials and certifications.

• 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.

🚀 Your main responsibilities:

• Develop and maintain a high-performance data processing platform for automotive data, ensuring scalability and reliability.

• Design and implement data pipelines that process large volumes of data in both streaming and batch modes.

• Optimize data workflows to ensure efficient data ingestion, processing, and storage using technologies such as Spark, Cloudera, and Airflow.

• Work with data lake technologies (e.g., Iceberg) to manage structured and unstructured data efficiently.

• Collaborate with cross-functional teams to understand data requirements and ensure seamless integration of data sources.

• Monitor and troubleshoot the platform, ensuring high availability, performance, and accuracy of data processing.

• Leverage cloud services (AWS) for infrastructure management and scaling of processing workloads.

• Write and maintain high-quality Python (or Java/Scala) code for data processing tasks and automation.

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

• At least 5 years of commercial experience implementing, developing, or maintaining Big Data systems, data governance and data management processes.

• Strong programming skills in Python (or Java/Scala): writing a clean code, OOP design.

• Hands-on with Big Data technologies like Spark, Cloudera, Data Platform, Airflow, Kafka, NiFi, Docker, and Iceberg.

• Excellent understanding of dimensional data and data modeling techniques.

• Experience implementing and deploying solutions in cloud environments.

• Consulting experience with excellent communication and client management skills, including prior experience directly interacting with clients as a consultant.

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

• Fluent in English (at least C1 level).

• Bachelor’s degree in technical or mathematical studies.

➕ Nice to have:

• Experience with an MLOps framework such as Kubeflow or MLFlow.

• Familiarity with Databricks and/or dbt.

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).