Data Engineer (Databricks)

Opis oferty

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.

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:

• 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.

Discover our perks and 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.
  

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

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.

Wymagania

What you’ll need to succeed in this role:

• At least 3 years of commercial experience implementing, developing, or maintaining Big Data systems.
• Strong programming skills in Python: writing a clean code, OOP design.
• Strong SQL skills, including performance tuning, query optimization, and experience with data warehousing solutions.
• Experience in designing and implementing data governance and data management processes.
• Deep expertise in Big Data technologies, including Databricks, Spark, Airflow, Kafka, and other modern data orchestration and transformation tools.
• Experience implementing and deploying solutions in cloud environments (with a preference for Azure).
• Knowledge of how to build and deploy Power BI reports and dashboards for data visualization.
• Excellent understanding of dimensional data and data modeling techniques.
• Consulting experience and the ability to guide clients through architectural decisions, technology selection, and best practices.
• Ability to work independently and take ownership of project deliverables.
• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or a related field.

Zakres obowiązków

• Design and optimize scalable data processing pipelines for both streaming and batch workloads using Big Data technologies such as Databricks, Apache Airflow, and Dagster.
• Architect and implement end-to-end data platforms, ensuring high availability, performance, and reliability.
• Lead the development of CI/CD and MLOps processes to automate deployments, monitoring, and model lifecycle management.
• Develop and maintain applications for aggregating, processing, and analyzing data from diverse sources, ensuring efficiency and scalability.
• Collaborate with Data Science teams on Machine Learning projects, including text/image analysis, feature engineering, and predictive model deployment.
• Design and manage complex data transformations using Databricks, DBT, and Apache Airflow, ensuring data integrity and consistency.
• Translate business requirements into scalable and efficient technical solutions while ensuring optimal performance and data quality.
• Ensure data security, compliance, and governance best practices are followed across all data pipelines.