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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 and analysis on AWS, utilizing tools such as Apache Spark (PySpark), Python, and SQL. Proficient in data-flow orchestration with Airflow and containerization technologies like Docker and ECS.
Highest-signal resume keywords
AWS Data EngineeringApache Spark (PySpark)Python ProgrammingSQL ProgrammingData-Flow Orchestration with Airflow
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 AnalysisApache Spark (PySpark)PythonSQLAirflowDockerECSKafkaDbt
Tools & Technologies
QlikViewQlikSenseDatabricksAgile Methodology
Tech Stack
Tools & technologiesAirflowApacheAWSDockerJavaKafkaPySparkPythonSparkSQL
About the role
Key responsibilities & impact- Join a stable project as an AWS Data Engineer
- Perform data engineering work
- Analyze data using AWS
- Develop and manage data flows using Airflow
- Work with containerization technologies including Docker and ECS
- Use Apache Spark (PySpark), Python, and SQL for data engineering tasks
- Potentially work with Kafka, dbt, Java, databases, QlikView, QlikSense, Databricks, and agile methodologies
Requirements
What you’ll need- Experience in data engineering
- Experience in data analysis on AWS
- Experience with Apache Spark (PySpark)
- Programming experience with Python and SQL
- Good knowledge of data-flow orchestration with Airflow
- Knowledge of containerization technologies, including Docker and ECS
- English B2, oral and written
- Experience with open-source tools such as Kafka and dbt is valued
- Java programming and database experience is valued
- Experience with QlikView and QlikSense is valued
- Experience with Databricks is valued
- Experience with agile methodology is valued
Benefits
Comp & perks- Remote work / telework from anywhere in Spain
