Data Architect / Platform Specialist – Enterprise, Databricks
Kyriba
AWSCloudETL
Mid-Level Data Engineer
Kyriba
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇵🇱 Poland
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSETLPythonPyTorchScalaScikit-LearnSQLTensorflow
About the role
- Design, implement, and optimize ETL pipelines using Databricks and AWS S3 to support analytics, ML, BI, and automation
- Build and maintain data architectures for structured and unstructured data, ensuring data quality, lineage, and security
- Integrate data from multiple sources including external APIs and on-premise systems to create a unified data environment
- Collaborate with Data Scientists and ML Engineers to deliver datasets and features for model training, validation, and inference
- Develop and operationalize ML/GenAI pipelines, automating data preprocessing, feature engineering, model deployment, and monitoring (e.g., Databricks MLflow)
- Support deployment and maintenance of GenAI models and LLMs in production environments
- Provide clean, reliable data sources for reporting and dashboarding via QlikView and enable self-service BI
- Partner with Automation Specialists to design and implement data-driven automated workflows using MuleSoft
- Implement data governance, security, and compliance best practices and document data flows, pipelines, and architectures
- Collaborate across teams (data science, BI, business, IT) to align data engineering efforts with strategic objectives
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field
- Proven experience as a Data Engineer or similar role (3+ years)
- Expertise in Databricks and AWS S3
- Strong programming skills in Python (preferred for ML/automation), SQL, and/or Scala
- Experience building data pipelines for analytics, ML, BI, and automation use cases
- Familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch) and MLOps tools (Databricks MLflow, AWS SageMaker)
- Familiarity with GenAI libraries (HuggingFace, LangChain) and LLM deployment
- Experience supporting BI/reporting solutions, preferably with QlikView
- Hands-on experience with automation/integration platforms such as MuleSoft is a strong plus
- Understanding of data governance, security, quality, and compliance
- Excellent communication, collaboration, and problem-solving skills
- Nice to have: experience deploying GenAI/LLM models at scale; API development; DevOps/CI/CD for data solutions; relevant AWS, Databricks, or QlikView certifications
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
ETL pipelinesDatabricksAWS S3PythonSQLScalaML frameworksMLOps toolsGenAI librariesdata pipelines
Soft skills
communicationcollaborationproblem-solving
Certifications
AWS certificationDatabricks certificationQlikView certification