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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data engineering with a focus on designing and implementing data processing solutions using Databricks, Python, and cloud platforms. Proficient in ensuring data consistency, security, and scalability while leveraging modern data frameworks and DevOps practices.
Highest-signal resume keywords
Databricks ExpertisePython ProficiencyCloud Platform ExperienceSQL KnowledgeReal-Time Data Streaming
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringData Processing SolutionsData Pipeline DevelopmentSQL Query OptimizationPySparkData ModelingAutomationData TransformationInfrastructure as CodeCloud Storage Solutions
Soft Skills
Strong Communication Skills
Tools & Technologies
AWSAzureGCPKafkaSpark StreamingTerraformBicepData LakeSnowflakeSynapse
Certifications & Qualifications
Databricks Certified Data Engineer Associate
Industry Keywords
DevOps MethodologiesCI/CD PipelinesCloud-Based EnvironmentsData ConsistencyData Security
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformKafkaPySparkPythonSparkSQLTerraform
About the role
Key responsibilities & impact- Design and implement data processing solutions using Databricks for large-scale and diverse datasets
- Design, build, and enhance data pipelines with Python and cloud-native tools
- Work closely with solution architects to define and uphold best practices in data engineering
- Ensure data consistency, security, and scalability within cloud-based environments
- Build scalable architectures for processing large and complex datasets across AWS, Azure, and GCP
- Leverage modern data frameworks, programming methodologies, and DevOps best practices
Requirements
What you’ll need- 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
- 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