Posted:3 weeks ago|
Platform:
On-site
Part Time
Description Design, develop, and maintain scalable and robust data solutions in the cloud using Apache Spark and Databricks. Gather and analyse data requirements from business stakeholders and identify opportunities for data-driven insights. Build and optimize data pipelines for data ingestion, processing, and integration using Spark and Databricks. Ensure data quality, integrity, and security throughout all stages of the data lifecycle. Collaborate with cross-functional teams to design and implement data models, schemas, and storage solutions. Optimize data processing and analytics performance by tuning Spark jobs and leveraging Databricks features. Provide technical guidance and expertise to junior data engineers and developers. Stay up to date with emerging trends and technologies in cloud computing, big data, and data engineering. Contribute to the continuous improvement of data engineering processes, tools, and best practices. Benefits Bachelor’s or master’s degree in computer science, engineering, or a related field. 10+ years of experience as a Data Engineer, Software Engineer, or similar role, with a focus on building cloud-based data solutions. Strong experience with cloud platforms such as Azure or AWS. Proficiency in Apache Spark and Databricks for large-scale data processing and analytics. Experience in designing and implementing data processing pipelines using Spark and Databricks. Strong knowledge of SQL and experience with relational and NoSQL databases. Experience with data integration and ETL processes using tools like Apache Airflow or cloud-native orchestration services. Good understanding of data modelling and schema design principles. Experience with data governance and compliance frameworks. Excellent problem-solving and troubleshooting skills. Strong communication and collaboration skills to work effectively in a cross-functional team.
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