Data Engineering Manager

Data Engineering Manager

Roles and Responsibilities:

• Provide business domain leadership, offering functional expertise in areas like Commercial, Finance, Supply Chain, and Customer Experience.
• Identify strategic analytics opportunities and cultivate executive relationships.
• Lead the development, delivery, and support for the Enterprise Data Warehouse, Analytics, DataOps, Data/AI Applications, and data pipelines.
• Manage and mentor technical contract service workers, establishing standards, innovative approaches, and best practices.
• Oversee metadata catalogs and report enhancement initiatives while establishing robust data quality standards.
• Lead efforts in observability and lineage tracking to maintain high integrity in AI/ML datasets.
• Identify whitespace opportunities for analytics and data engineering, manage idea backlogs, and drive strategic initiatives that deliver measurable business value.
• Lead business committees, manage expectations, and establish strong partnerships between technical teams and business functions.
• Optimize analytics asset inventory and streamline requirements gathering processes to ensure high-quality, business-aligned deliverables.
• Establish frameworks for vendor management and technical escalation procedures with clear accountability.

Skills Requirement:

• Advanced knowledge of modern data engineering tools and practices.
• Intermediate-level proficiency in languages such as SQL, Python, and Spark.
• Strong business process and domain knowledge across multiple functions, with the ability to translate business requirements into analytics solutions.
• Prior experience with enterprise-scale platforms, including Snowflake or similar Data Warehouses, Databricks or similar AI/ML Platforms, and Informatica Intelligent Cloud Services, HVR, Fivetran, or similar Data Ingestion and Transformation Tools.
• Experience and domain knowledge of enterprise systems of record such as SAP, Salesforce CRM, and eCommerce Systems, along with associated end-to-end processes.
• Strong background in enterprise analytics with a focus on measurable business outcomes.
• Proficient in converting complex business insights into relevant data products, while maintaining effective relationships with business partners.
• Experience implementing quality assurance and user acceptance testing processes for analytics deliverables.
• Strong experience in requirements gathering, project prioritization, and managing competing business demands.
• Exceptional presentation and communication skills with the ability to influence at all levels of the organization.
• Demonstrated success in managing initiatives across organizational boundaries and building consensus.
• Experience managing vendor relationships and service transitions.
• Familiarity with IT Operations, ITIL practices, and other service management frameworks.

QUALIFICATION:

• Bachelor's or Master's degree in Computer Science, Engineering, Applied Mathematics, or a related field.