Data Integration Specialist

Data Integration Specialist

Job Summary:

We are seeking a skilled Data Integration Specialist with over 7 years of experience to join our dynamic team. This role is pivotal in enabling seamless data integration processes and working with cutting-edge technologies to enhance our client's data management capabilities.

Key Responsibilities:

• Design and implement data integration workflows using Azure Data Lake Storage (ADLS) and Azure Data Factory (ADF).
• Develop ETL processes to efficiently move data from various sources into ADLS.
• Collaborate with cross-functional teams to understand data requirements and ensure best practices in data integration.
• Monitor and optimize data flows and troubleshoot integration issues to enhance system reliability.
• Document integration processes and maintain updated records of data transformation rules and mapping.
• Participate in all phases of the project lifecycle, from requirements gathering to deployment and support.
• Prepare for and actively participate in multiple rounds of technical interviews, demonstrating expertise and problem-solving skills.

Requirements:

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• A minimum of 7 years of experience in data integration roles, with a strong focus on ADLS and ADF.
• Proficiency in scripting languages such as Python or PowerShell for automation tasks.
• Strong understanding of data warehousing concepts and data modeling techniques.
• Experience with data governance and quality assurance practices.
• Excellent analytical and problem-solving skills, with the ability to work independently and as part of a team.
• Effective communication skills, with the ability to articulate technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience in Azure cloud services beyond ADLS and ADF, such as Azure Synapse Analytics.
• Familiarity with Agile methodologies and DevOps practices in data operations.
• Certification in Azure Data Engineering or related fields is a plus.
• Background in big data technologies and tools (e.g., Spark, Hadoop) is beneficial.