Data Engineer – Databricks

Job not on LinkedIn

🕒 March 31

🇵🇱 Poland – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 49%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Addepto

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

🏥 Healthcare

Consulting • Logistics • Healthcare

Addepto is a company specializing in Artificial Intelligence and Machine Learning solutions tailored for various industries. They offer AI consulting, MLOps consulting, and data engineering services, providing comprehensive AI-driven strategies and applications. Addepto focuses on implementing sophisticated AI technologies such as Generative AI, computer vision, and large language models to solve complex business problems. They cater to industries like finance, aviation, retail, and logistics, among others, enhancing operations and decision-making processes.

📋 Description

• 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.

🎯 Requirements

• 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. • Experience in designing and implementing data governance and data management processes. • Familiarity with Big Data technologies like Airflow or Dagster, Databricks, Spark and DBT. • 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. • 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.

🏖️ 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 make use of 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.