Lead Data Engineer

We are seeking a talented and experienced Senior Data Engineer to join our team and contribute to building a robust data platform on Azure Cloud. The ideal candidate will have hands-on experience designing and managing data pipelines, ensuring data quality, and leveraging cloud technologies for scalable and efficient data processing. The Data Engineer will design, develop, and maintain scalable data pipelines and systems to support the ingestion, transformation, and analysis of large datasets. The role requires a deep understanding of data workflows, cloud platforms (Azure), and strong problem-solving skills to ensure efficient and reliable data delivery.

Key Responsibilities

1. Data Ingestion and Integration:

2. Develop and maintain data ingestion pipelines using tools like Azure Data Factory, Databricks, and Azure Event Hubs.

3. Integrate data from various sources, including APIs, databases, file systems, and streaming data.

4. ETL/ELT Development:

5. Design and implement ETL/ELT workflows to transform and prepare data for analysis and storage in the data lake or data warehouse.

6. Automate and optimize data processing workflows for performance and scalability.

7. Data Modeling and Storage:

8. Design data models for efficient storage and retrieval in Azure Data Lake Storage and Azure Synapse Analytics.

9. Implement best practices for partitioning, indexing, and versioning in data lakes and warehouses.

10. Quality Assurance:

11. Implement data validation, monitoring, and reconciliation processes to ensure data accuracy and consistency.

12. Troubleshoot and resolve issues in data pipelines to ensure seamless operation.

13. Collaboration and Documentation:

14. Work closely with data architects, analysts, and other stakeholders to understand requirements and translate them into technical solutions.

15. Document processes, workflows, and system configurations for maintenance and onboarding purposes.

16. Cloud Services and Infrastructure:

17. Leverage Azure services like Azure Data Factory, Databricks, Azure Functions, and Logic Apps to create scalable and cost-effective solutions.

18. Monitor and optimize Azure resources for performance and cost management.

19. Security and Governance:

20. Ensure data pipelines comply with organizational security and governance policies.

21. Implement security protocols using Azure IAM, encryption, and Azure Key Vault.

22. Continuous Improvement:

23. Monitor existing pipelines and suggest improvements for better efficiency, reliability, and scalability.

24. Stay updated on emerging technologies and recommend enhancements to the data platform.

Skills

• Strong experience with Azure Data Factory, Databricks, and Azure Synapse Analytics.
• Proficiency in Python, SQL, and Spark.
• Hands-on experience with ETL/ELT processes and frameworks.
• Knowledge of data modeling, data warehousing, and data lake architectures.
• Familiarity with REST APIs, streaming data (Kafka, Event Hubs), and batch processing.

Good To Have:

• Experience with tools like Azure Purview, Delta Lake, or similar governance frameworks.
• Understanding of CI/CD pipelines and DevOps tools like Azure DevOps or Terraform.
• Familiarity with data visualization tools like Power BI.

Competency

• Analytical Thinking
• Clear and effective communication
• Time Management
• Team Collaboration
• Technical Proficiency
• Supervising Others
• Problem Solving
• Risk Management
• Organizing & Task Management
• Creativity/innovation
• Honesty/Integrity

Education:

• Bachelors degree in Computer Science, Data Science, or a related field.
• 8+ years of experience in a data engineering or similar role.