Job Summary: We are seeking a skilled Data Engineer with a solid background in Azure Synapse Analytics and data engineering practices. The ideal candidate will have hands-on experience with Python and Spark-based systems, as well as proficiency in utilizing Power Apps for data solutions. This role involves working closely with cross-functional teams to design, implement, and optimize data pipelines and analytics solutions.
Responsibilities:
- Design, develop, and maintain data pipelines using Azure Synapse Analytics and Azure Data Factory.
- Implement and optimize data processing workflows using Apache Spark.
- Utilize Power Apps to create user-friendly applications for data management and reporting.
- Manage dedicated SQL servers and serverless SQL environments to ensure data accessibility and performance.
- Provide UAT support, performance optimization, and debugging for data solutions.
- Collaborate with data scientists and analysts to integrate machine learning models into data pipelines.
- Document processes, data flows, and technical specifications for future reference.
Mandatory Skills:
- Proven experience with Azure Synapse Analytics.
- Strong proficiency in Python and Spark-based systems.
- Hands-on experience with Power Apps.
- Experience with dedicated SQL servers and serverless SQL.
- Knowledge of Azure Data Factory and Synapse pipelines.
- Expertise in Apache Spark pool management.
Preferred Skills:
- Familiarity with machine learning concepts and statistical analysis.
- Experience in performance optimization and debugging of data solutions.
Qualifications:
- Bachelors degree in Computer Science, Information Technology, or a related field.
- 6-8 years of relevant experience in data engineering or a similar role.
- Robust analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.