Senior Data Platform Engineer
New
H
Holisticon InsightData Consulting
Location of candidate in Poland or other EU countryContractSenior
Salary150 - 180 PLN per hour
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Job Details
- Languages
- English
- Experience
- 5+ years
- Required Skills
- PythonSQLCI/CDRESTful APIsDevOpsPySpark
Requirements
- 5+ years of professional experience as a Data Engineer or in a similar role.
- Strong hands-on experience with Databricks and modern data platform development.
- Solid experience with Azure Data Factory and the broader Azure data ecosystem.
- Good understanding of DataOps, DevOps practices, CI/CD pipelines, and infrastructure maintenance.
- Experience in processing data from various sources, including relational and non-relational databases and REST APIs.
- Experience designing and implementing data architectures and scalable data processing solutions.
- Strong SQL skills and proficiency in Python for data engineering workloads.
- Experience supporting production environments, deployments, monitoring, and troubleshooting.
- Familiarity with data streaming technologies and real-time data processing concepts.
- Experience working in consulting environments or in roles requiring high ownership.
- Strong collaboration skills and willingness to mentor junior team members.
- Excellent English communication skills.
- Location of candidate in Poland or other EU country.
Responsibilities
- Design, develop, and maintain scalable data pipelines and data platform solutions using Azure technologies.
- Build and enhance new features for the client's growing data platform while ensuring high quality and maintainability.
- Take ownership of technical decisions, architecture design, and implementation of data solutions from concept to production.
- Collaborate closely with data scientists, business stakeholders, and technical teams to deliver reliable data products.
- Support and mentor less experienced data engineers by sharing knowledge and promoting engineering best practices.
- Manage production deployments, monitor platform performance, and ensure operational stability of data services.
- Contribute to platform maintenance, troubleshooting, and continuous improvements across the data ecosystem.
- Design, develop, and optimize streaming and batch data processing pipelines for large-scale datasets.
- Identify priorities and implement solutions in a highly autonomous environment.
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