Databricks Data Engineer | Latvia - - 18843

Ogólne informacje

Stanowisko

Databricks Data Engineer | Latvia

Wymiar czasu pracy

Pełny wymiar czasu pracy

Miasto

Ryga

Kraj

Łotwa

Dział

Consulting

Zespół

Engineering, AI & Data

Obszar zainteresowania

Engineering, IT - Development

Tryb pracy

Hybrydowy

Opis i wymagania

Who we are looking for

🎯We are looking for a Data Engineer with Databricks expertise to join our growing AI & Data team in Latvia. This role is ideal for someone with a strong foundation in data engineering who wants to deepen their skills in Databricks, cloud platforms, and modern data architectures while working on impactful projects across industries.

💼 What we’re looking for

2–3 years of experience in data engineering or related field.
Bachelor’s degree in Computer Science, Engineering, or related field.
Hands-on experience with Databricks (PySpark, Delta Lake, SQL).
Proficiency in Python and/or SQL for data manipulation.
Familiarity with cloud platforms (Azure, AWS, or GCP).
Strong problem-solving skills and eagerness to learn new technologies.
Fluency in English are required

Your future role

Build and optimize data pipelines and ETL processes using Databricks.
Collaborate with data scientists and analysts to design scalable data solutions.
Ensure data quality, consistency, and performance across multiple sources.
Work with cloud environments (Azure, AWS, or GCP) to deploy and manage data solutions.
Participate in requirement gathering sessions with clients to understand business needs and translate them into technical solutions.
Develop and maintain data models, documentation, and best practices for data management.
Troubleshoot data-related issues and provide support for production systems.
Contribute to proof-of-concepts and pilots for new technologies within the data landscape.
Collaborate with cross-functional teams in a consulting environment to deliver end-to-end data solutions.

What we offer

Competitive compensation and benefits package.
A role in an international AI & Data practice with exposure to diverse projects.
Career growth and continuous learning opportunities with certifications and training.
Remote working model.
Collaborative, innovative, and supportive team culture.