
Lead Enterprise Software Engineer
2 days ago
Responsibilities:
Collaborate with cross-functional teams and project stakeholders to capture data and analytic use cases and requirements for projects or operational support across various Wolters Kluwer business units. Build trust with business stakeholders/SMEs to extract requirements and, when necessary, influence them toward the appropriate solution. Work with ETL developers, report designers, and data teams to deliver the right data solution based on best practices, security, and quality standards. Use strong communication skills, problem-solving abilities, and best practice knowledge to guide the development team, ensuring alignment with business analytic objectives. Provide clear written and verbal communication on status updates and escalate issues/risks as necessary. Lead others in resolving complex technical problems using advanced analytical thinking; ensure Operations teams deliver on enhancement requests, identify root causes, resolve defects, and improve processes. Design and optimize ETL workflows, ensuring scalability, performance, and reliability.Required experience:
Education: Bachelor’s Degree in computer science or a related field is required. Experience: A minimum of 10+ years of broad Information Technology experience. Expertise in Informatica ETL/data integration and data reporting/analytic processes, technologies, and architectures. Deep understanding of data warehouse design and data modeling. Strong knowledge of RDBMS (Oracle, DB2, MySQL, or SQL Server), including data modeling and datamart design. Expertise in ETL tools such as Informatica Powercenter and IICS. Good knowledge in unix scripting. Experience with cloud-based data warehousing solutions (e.g., Snowflake, AWS Redshift, Google BigQuery) is a plus. Proficient in analyzing business needs, including scheduling meetings, planning agendas, consulting with business leaders, and delivering presentations to senior management, peer groups, and associates. Can collaborate with data architects, data analysts, and business stakeholders to understand data requirements and ensure data accuracy, integrity, and consistency.-
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