
Principal Data Architect
4 days ago
We are seeking an experienced Data Engineer to play a critical role in designing, developing, and maintaining our data pipelines and infrastructure.
As a key member of the team, you will work closely with data scientists, analysts, and other stakeholders to ensure data is accurate, timely, and accessible. Your contributions will directly impact our data-driven decision-making and support our growth.
Key Responsibilities:
- Design, develop, and implement data pipelines using Azure Data Factory and Databricks to support the ingestion, transformation, and movement of data.
- Develop and optimize ETL (Extract, Transform, Load) processes to ensure efficient data flow and transformation.
- Develop and maintain Azure Data Lake solutions, ensuring efficient storage and retrieval of large datasets.
- Work with Azure Synapse Analytics to build and manage scalable data warehousing solutions that enable advanced analytics and reporting.
- Integrate various data sources into MS-Fabric, ensuring data consistency, quality, and accessibility across different platforms.
- Optimize data processing workflows and storage solutions to improve performance and reduce costs.
- Manage and optimize databases (SQL and NoSQL) to support high-performance queries and data storage requirements.
- Implement data quality checks and monitoring to ensure accuracy and consistency of data.
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver actionable insights.
- Create and maintain comprehensive documentation for data processes, pipelines, and infrastructure, architecture and best practices.
- Identify and resolve issues in data pipelines, data lakes, and warehousing solutions, providing timely support and maintenance.
Qualifications:
- 2-4 years of experience in data engineering or a related field.
- Proficiency with Azure Data Factory, Azure Synapse Analytics, Databricks, and Azure Data Lake.
- Experience with Microsoft Fabric is a plus.
- Strong SQL skills and experience with data warehousing concepts (DWH).
- Knowledge of data modeling, ETL processes, and data integration.
- Experience with relational databases (e.g., MS-SQL, PostgreSQL, MySQL).
- Hands-on experience with ETL tools and frameworks (e.g., Apache Airflow, Talend).
- Knowledge of big data technologies (e.g., Hadoop, Spark) is a plus.
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and associated data services (e.g., S3, Redshift, BigQuery).
- Familiarity with data visualization tools (e.g., Power BI) and experience with programming languages such as Python, Java, or Scala.
- Experience with schema design and dimensional data modeling.
- Strong problem-solving abilities and attention to detail.
- Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.
- Bachelor's degree in computer science, Engineering, Mathematics, or a related field. Advanced degrees or certifications are a plus.
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