
Principal Data Architect
2 days ago
At the forefront of data engineering lies a pivotal role, that of crafting efficient and scalable pipelines for seamless data accessibility.
Data Engineering: A Comprehensive OverviewWe are in search of an astute Data Engineer with profound expertise in Spark and SQL to spearhead our mission-critical projects.
This position entails the responsibility of designing, implementing, and optimizing data pipelines on our Data platform. Collaboration with data architects and other stakeholders is crucial to ensure data reliability, accessibility, and performance.
Main Responsibilities:
- Data Pipeline Development: Design, develop, and maintain data pipelines utilizing Azure Synapse, Databricks & Apache Spark (PySpark).
- Data Integration: Consolidate disparate data sources, ensuring integrity and consistency.
- Performance Optimization: Enhance data processing workflows for efficiency and cost-effectiveness.
- Collaboration: Work with cross-functional teams to understand data requirements and deliver solutions.
- Monitoring and Troubleshooting: Monitor data pipelines and troubleshoot issues to guarantee data integrity.
- Documentation: Document data workflows, processes, and best practices.
Technical Requirements:
- Proficiency in Azure Synapse/Databricks and Apache Spark.
- Strong PySpark and SQL skills for data manipulation and querying.
- Familiarity with Delta Live Tables and Databricks workflows.
- Experience with ETL tools and processes.
- Knowledge of cloud platforms (AWS, Azure, GCP).
- Minimum 2 years of work experience with Azure Synapse.
- 5 years of experience in data engineering.
Benefits:
- Opportunities for growth and professional development.
- Collaborative and dynamic work environment.
- Competitive compensation package.
Additional Information:
The ideal candidate will have experience working with Azure Synapse, Databricks, and Apache Spark, as well as strong problem-solving and communication skills.
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