Data Engineer
Skills
SQLArtificial IntelligencePythonSparkETL/ELTDatabricksSnowflake
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Strong background building and operating large-scale cloud-native data platforms
- Experience with high-volume distributed data systems
- Proven ability to develop scalable ETL and ELT pipelines
- Strong expertise with SQL Python and Spark
- Experience with cloud platforms such as AWS GCP or Azure
- Hands-on experience with Databricks Snowflake Kafka Airflow Hive Delta Lake or similar platforms
- Strong understanding of data modeling data warehousing orchestration and data governance
- Excellent problem-solving communication and cross-functional collaboration skills
- Experience supporting data platforms used for analytics machine learning or large-scale business operations
Nice to have
- Large-scale experience
- Cloud-native mindset
- Cross-functional collaborator
- Operational excellence
Day to day
- Design, build, and maintain highly scalable fault-tolerant data pipelines and distributed data platforms.
- Develop robust ETL and ELT frameworks for processing large volumes of structured and unstructured data.
- Architect data solutions that support analytics reporting AI and ML and real-time business insights.
- Optimize data models storage and processing for performance reliability and scalability.
- Partner with cross-functional teams to deliver data-driven solutions and improve data quality governance and operational excellence.