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Azure Data Engineer

Syntricate Technologies

Dallas, TX
Azure Data Engineer

Dallas TX (Hybrid 3 days in a week)

12+ Months

Web Cam Interview

Requirement Notes (Candidate Job description below) :
  • We need a senior (10+ years) Azure Data engineer with recent experience in Banking, Capital Markets or Financial services.
  • Candidates must have recent experience working with Azure Data Factory (ADF) and Azure Databricks in a Financial environment.
  • Candidates must have excellent communication skills/no accent.


Experience required on a resume and for submittal:
  • How many years working with: Azure Data Engineer
  • How many years working with: Azure Data Factory (ADF)
  • How many years working with: Azure Databricks (highlighted expertise)
  • How many years working with: Banking, Capital Markets or Financial services OR FORTUNE 500


Education:
  • Bachelor's or Master's degree in Computer Science, Information Technology, or a related field (Engineering or Math preferred).
Technical Skills:

Programming & Tools:
  • 10+ years of experience in SQL, Python. .Net is a plus.
  • 3+ years of experience in Azure cloud services , including:
  • Azure SQL Server
  • Azure Data Factory (ADF)
  • Azure Databricks (highlighted expertise)
  • Azure Data Lake Storage (ADLS)
  • Azure Key Vault
  • Azure Functions
  • Logic Apps
  • 3+ years of experience in GIT and deploying code using CI/CD pipelines.
Certifications (Preferred):
  • Microsoft Certified: Azure Data Engineer Associate
  • Databricks Certified Data Engineer Associate or Professional
Soft Skills:
  • Strong analytical and problem-solving skills.
  • Excellent communication and interpersonal skills.
  • Ability to work independently and collaboratively within a team.
  • Attention to detail and a commitment to delivering high-quality work.
Responsibilities:

Data Pipeline Development:
  • Create and manage scalable data pipelines to collect, process, and store large volumes of data from various sources.
Data Integration:
  • Integrate data from multiple sources, ensuring consistency, quality, and reliability.
Database Management:
  • Design, implement, and optimize database schemas and structures to support data storage and retrieval.
ETL Processes:
  • Develop and maintain ETL (Extract, Transform, Load) processes to ensure accurate and efficient data movement between systems.
Data Warehousing:
  • Build and maintain data warehouses to support business intelligence and analytics needs.
Performance Optimization:
  • Optimize data processing and storage performance for efficient resource utilization and quick data retrieval.
Documentation:
  • Create and maintain comprehensive documentation for data pipelines, ETL processes, and database schemas.
Monitoring and Troubleshooting:
  • Monitor data pipelines and systems for performance and reliability, troubleshooting and resolving issues as they arise.
Technology Evaluation:
  • Stay updated with emerging technologies and best practices in data engineering, evaluating and recommending new tools and technologies as appropriate.
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Vacancy posted more than 2 months ago

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