App Tech Specialist - ETL- Data Integration

Responsibilities: Requirements Gathering and Documentation 

• Gather, analyze, and document data integration requirements and translate those requirements into functional and technical solutions
• Ensure clear and comprehensive documentation detailing project specifications and objectives, ETL processes, data models, and data lineage

Technical and Non-Technical Collaboration

• Bridge the gap between technical and non-technical stakeholders, translating business needs into technical specifications
• Facilitate communication and understanding between clients, stakeholders, and the data analytics team

Data Integration Design 

• Lead the design and architecture of data integration solutions, aligning them with project goals and adhering to industry best practices 
• Strategize and develop data models, integration processes, and transformations to consolidate data from disparate sources 

Testing and Quality Assurance

• Conduct extensive testing and quality assurance to ensure the accuracy and reliability of data integration solutions
• Implement comprehensive data validation procedures to maintain data integrity

Complex Issue Troubleshooting 

• Investigate and resolve complex data integration issues using advanced troubleshooting skills and technical expertise
• Proactively identify potential challenges in data integration to minimize operational disruptions

Education and Experience: 

• Minimum of a bachelor's degree in Computer Science, Information Technology, Data Science, or a related field
• Minimum of five years of proven experience in data integration and leading complex data integration projects, including requirement gathering, design, testing, and quality assurance

Technical Skills:

• Expert knowledge of data integration tools and technologies like ETL platforms, APIs, data warehousing, transformation tools, and related software
• Proficiency in designing and building data models that efficiently consolidate data from disparate sources
• Strong understanding of scripting languages like SQL or Python for data manipulation and transformations
• Expertise in data quality testing, validation, and cleansing techniques
• Advanced troubleshooting skills to identify and resolve complex data integration issues