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Senior Data Solutions Engineer
2 weeks ago
We are a leading Google Cloud Premier Partner, with a focus on innovative Microsoft Azure projects.
As a key member of our team, you will be responsible for designing and maintaining robust, scalable data platforms using a variety of Azure services.
Our team believes great engineering requires heart and dedication to building solutions that guide our clients through their digital transformation journey.
Responsibilities- Data Pipeline Development: Design, build, and maintain data pipelines to ingest, transform, and load data from various sources into the Azure data platform.
- Data Modeling and Warehousing: Develop conceptual, logical, and physical data models for data warehouses and data lakes.
- Data Lake Management: Manage data storage and organization within Azure Data Lake Storage Gen2.
- Data Transformation: Utilize tools like dbt to transform raw data into analytics-ready datasets.
- Azure Service Integration: Integrate and work with Azure services such as Synapse Analytics, Databricks, Functions, and Cosmos DB.
- ETL/ELT Processes: Implement and optimize ETL and ELT processes to ensure data is moved efficiently and accurately.
- Security and Governance: Implement data security best practices and apply RBAC, managed identities, and Azure Key Vault to protect sensitive data.
- Performance Optimization: Monitor and optimize data pipeline performance, queries, and data warehouse solutions.
- 4+ years of experience with key Azure data services.
- Strong proficiency in SQL and at least one programming language such as Python or Spark.
- Solid understanding of data warehousing principles, data modeling, and ETL concepts.
- CI/CD: Experience with version control systems like Git and Continuous Integration/Continuous Deployment practices.
- Ability to work effectively with cross-functional teams to understand requirements and deliver data solutions.
- Excellent analytical and problem-solving skills with a focus on delivering high-quality, reliable data solutions.
This role requires strong hands-on engineering skills to implement data pipelines, manage data integrity, and ensure compliance with security and governance standards.
