Senior Databricks Data Engineer
At a glance
Senior Data Engineering role at OPTIVEUM sp. z o.o. Warsaw · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build Databricks solutions to process large, varied datasets at scale
- Create and improve Python-based data pipelines using tools native to cloud platforms
- Work with solution architects to set and maintain data engineering practices
- Protect data consistency and security while keeping cloud systems scalable
What you bring
- You have commercial data engineering experience and practical Databricks skills
- You are proficient in Python for automation and transforming data
- You have commercial experience with AWS, Azure or GCP
- You communicate well and have advanced English and Polish
Who this fits
This senior role suits an experienced data engineer with Databricks and cloud-platform experience. The position is fully remote within Poland and uses a B2B contract.
From the employer
Senior Databricks Data Engineer
Location: 100% Remote (Poland)
Rate: up to 38 EUR + VAT (B2B) Work model: B2B Contract Contracting Party: Optiveum
Optiveum is currently looking for a Senior Databricks Data Engineer to join the team of our client—a thriving technology organization with over 400 professionals dedicated to delivering advanced, data-driven solutions.
In this role, you will be part of a team whose expertise lies in Cloud & Big Data engineering. You will help build scalable architectures for processing large and complex datasets across AWS, Azure, and GCP while leveraging modern data frameworks, programming methodologies, and DevOps best practices.
Please note: Optiveum acts as the recruitment partner and the direct contracting party for this position.
Your Tasks:
Designing and implementing data processing solutions using Databricks for large-scale and diverse datasets.
Designing, building, and enhancing data pipelines with Python and cloud-native tools.
Working closely with solution architects to define and uphold best practices in data engineering.
Ensuring data consistency, security, and scalability within cloud-based environments.
Your Profile:
Solid commercial experience in data engineering, coupled with hands-on Databricks expertise.
Strong proficiency in Python for automation and data transformation.
Commercial experience working with at least one major cloud platform (AWS, Azure, or GCP).
Strong communication skills.
Advanced command of both English and Polish.
Nice-to-Have:
Solid understanding of SQL, including experience in query optimization and data modeling.
Familiarity with DevOps methodologies, CI/CD pipelines, and Infrastructure as Code (Terraform, Bicep).
Experience with real-time data streaming technologies such as Kafka or Spark Streaming.
Knowledge of cloud storage solutions like Data Lake, Snowflake, or Synapse.
Hands-on experience with PySpark for distributed data processing.
Relevant industry certifications (e.g., Databricks Certified Data Engineer Associate or cloud-based data certifications).
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