Enterprise Software Engineer - Cloud Data Engineering

Enterprise Software Engineer

About the Role:

Under general supervision, oversees moderately complex data engineering and cloud data warehouse implementation projects.  Responsible for a variety of tasks to ensure deliverables are implemented on time and meet user requirements.  Activities may include development of work plan, identify appropriate tools and technology needed, coordinate activities of other project team members.  Ensures that implementations and related services are delivered on time and meet user requirements by maintaining control over the project scope and quality.

Responsibilities:

• Work with functional teams to successfully deliver on system design and development for the needed data integration and data management requirements supporting various Business Units.
• Work with cross-functional teams to implement cloud data management solutions (Snowflake) and data ingestion solutions to support various Business Units
• Work with GTS team to incorporate GenAI capabilities to deliver data ingestion pipelines and expedite data insights for users
• Work across the GBS organizations including teams responsible for requirements, solution architecture, quality assurance and production support for successful design and development of cloud data integration solutions
• Collaborate with business process owners to define analytic and data ingestion requirements
• Work closely with PMO, Quality Assurance, Production Support, and Client executives across various Business units.
• Ensure that solutions are being delivered per standards of availability, scalability, and security point of view, and that they are done on time with highest quality.
• Support Operations teams with job monitoring and delivering enhancements and defect fixes

Required experience:

• Education: Required: Bachelor’s degree in computer science or related field.
• Experience:  Minimum 4 - 6 years broad Information Technology experience
• 2-5 years’ experience designing and building data warehouse and data engineering solutions on cloud platform such as Snowflake and Informatica IDMC
• Maintain proficiency in ETL/data integration and information management processes, technologies and architectures: Dimensional data modeling principles, snowflake schemas, de-normalized data structures, slowly changing dimensions, etc.
• Strong hands-on experience with SQL query development and Python
• Solid understanding of latest GenAI solutions to deliver data engineering solutions
• Solid understanding of cloud data platforms (Snowflake, Fabric), including data modeling and DataMart design
• Analyzing business needs, including scheduling meetings, planning agendas, collaborating with business users to refine and deliver solutions.
• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.

Experience Level

Senior Level