Data Engineer II (with MLOps)
New
PolandFull-TimeMiddle
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Languages
- Fluent English, written and spoken
- Experience
- 2-4+ years in Data Engineering, Analytics Engineering, or a backend data-focused role
- Required Skills
- AWSPythonSQLData engineeringCI/CDA/B testingRedshiftAWS LambdaMLOps
Requirements
- A Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field — or equivalent practical experience
- 2-4+ years in Data Engineering, Analytics Engineering, or a backend data-focused role
- Hands-on experience designing and maintaining data pipelines and data warehouse solutions in AWS
- Strong SQL — efficient transformations, query optimization, and analytical data modeling
- Proficiency in Python for data processing and pipeline development
- Practical experience with ETL/ELT processes, data warehousing concepts (dimensional modeling), and data quality best practices
- Familiarity with core AWS services such as S3, Redshift, Lambda, and CloudWatch
- Awareness of ML data preparation and feature engineering workflows
- Strong analytical thinking, clear communication, and a collaborative mindset across distributed teams
- Fluent English, written and spoken
Responsibilities
- Design and maintain scalable batch data pipelines in AWS to power analytics and ML use cases.
- Develop and optimize SQL transformations and analytical datasets for BI and predictive workloads.
- Build reliable ETL/ELT processes with monitoring and data quality checks.
- Create feature-ready datasets and support feature engineering pipelines for ML initiatives.
- Deliver production-grade data to support elasticity modeling and advanced performance analytics.
- Design data infrastructure for A/B testing and measurable experimentation.
- Develop ingestion pipelines for marketing and campaign analytics.
- Contribute to CI/CD-driven MLOps workflows for model deployment and monitoring in AWS.
- Collaborate on data governance, cost optimization, and scalable architecture decisions.
- Enable integration of AI and LLM-powered capabilities through robust, future-ready data services.
View Full Description & ApplyYou'll be redirected to the employer's site
