Senior Azure Data Engineer
6 days ago
- Role Summary
The Senior Data Engineer role is responsible for designing, developing and maintaining data pipelines, databases and data infrastructure to enable the efficient data collection, storage and analysis. This role requires collaboration with data scientists, data infrastructure architects and data consumption stakeholders to ensure the availability of high-quality data for insights and decision making is available and will deliver value to the GM strategic vision for the future and meet prioritized business needs. This role drives to deliver innovative solutions with technical fidelity and thrives to work effectively across a cross-functional data and stakeholder ecosystem.
Key Responsibilities:
- Design, construct, install and maintain data architectures, including database and large-scale processing systems.
- Develop and maintain ELT (Extract, Load, Transform) processes to collect, cleanse and transform data from various sources inclusive of cloud
- Design and implement data pipelines to collect, process and transfer data from various sources to storage systems (data warehouses, data lakes, etc.
- Implement security measures to protect sensitive data and ensure compliance with data privacy regulations.
- Build data solutions that ensure data quality, integrity and security through data validation, monitoring, and compliance with data governance policies
- Maintain Master Data, Metadata, Data Management Repositories, Logical Data Models, and Data Standards
- Troubleshoot and resolve data-related issues affecting data quality fidelity
· Database Management: Design, optimize, and manage databases to ensure data integrity, performance, and scalability.
· Testing and Quality Assurance: Write unit tests, conduct code reviews, and implement automated testing frameworks to ensure the reliability and stability of applications.
· Continuous Integration and Deployment (CI/CD): Implement CI/CD pipelines using Azure DevOps or similar tools to automate build, test, and deployment processes.
· Performance Optimization: Identify and resolve performance bottlenecks, memory leaks, and other issues to ensure optimal application performance.
Qualifications:
- Strong skills in SQL, Python, Unix and ability to write efficient ETL on Kubernetes and Cloud platforms specifically Azure and Databricks
- Strong understanding and ability to provide mentorship in the areas of data ETL processes and tools for designing and managing data pipelines
- Experience with big data frameworks and tools like Apache Hadoop, Apache Spark, or Apache Kafka for processing and analyzing large datasets.
- Hands on experience with data serialization formats like JSON, Parquet and XML
- Hands on file processing experience dealing with CSV, SPSS and other standard formats
- Hands on experience with GIT Repository and Integrating code between Databricks and GIT environments
- Consistently designs solutions and build data solutions that are highly automated, performant, with quality checks that provide data consistency and accuracy outcomes
- Experience in actively managing large-scale data engineering projects, including planning, resource allocation, risk management, and ensuring successful project delivery and adjust style for all delivery methods (i.e.: Waterfall, Agile, POD, etc.)
- Understands data governance principles, data privacy regulations, and experience implementing security measures to protect data
- Ability to work effectively in cross-functional teams, collaborate with data scientists, analysts, and stakeholders to deliver data solutions
- Influential communication skills to effectively convey technical concepts to non-technical stakeholders and document data engineering processes
- Models a mindset of continuous learning, staying updated with the latest advancements in data engineering technologies, and a drive for innovation
- ·Bachelor’s degree in computer science, Engineering, or a related field. Master's degree preferred.
- ·5 to 7 years of experience as a Software Engineer with primary focus on Data Engineering.
- ·Hands-on experience with Azure cloud services, Azure Storage, Azure DevOps, etc.
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