Job Level
Senior
Tech Stack
AirflowApacheAWSAzureCloudETLNoSQLSparkSQL
About the role
- Design, develop, and maintain scalable and robust data solutions in the cloud using Apache Spark and Databricks.
- Gather and analyze 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.
- Collaborate with clients to optimize their data infrastructure and provide insights using advanced analytics.
Requirements
- Bachelor's or Master's degree in computer science, engineering, or a related field.
- 8+ years of experience as a Data Engineer, 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 modeling 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.
- Relevant certifications in cloud platforms, Spark, or Databricks are a plus.