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Data Engineer
Skills
Warehouse OperationsApache SparkData ArchitectureData WarehousingDatabasesEnhanced Data Rates For GSM EvolutionModeling
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years of experience as a Data Engineer
- Strong proficiency in Python and SQL
- Experience with ETL/ELT development and data integration
- Hands-on experience with Apache Spark PySpark and Kafka
- Experience with cloud platforms such as AWS Azure or GCP
- Knowledge of data warehousing concepts including Snowflake Redshift BigQuery or Synapse
- Experience with workflow orchestration tools like Apache Airflow
- Familiarity with relational and NoSQL databases including PostgreSQL MySQL MongoDB or DynamoDB
- Understanding of data modeling data governance and data quality best practices
- Experience with version control tools such as Git
- Strong analytical troubleshooting and problem-solving skills
Nice to have
- Databricks experience
- CI/CD exposure
- Docker and Kubernetes
- Agile/Scrum experience
Day to day
- Design, build, and maintain scalable data pipelines and ETL workflows for reliable data movement.
- Develop and optimize data ingestion processes from multiple sources while improving performance and efficiency.
- Collaborate with Data Scientists Analysts and Software Engineers to deliver high-quality data solutions and support production stability.