Data Leader/Delivery Manager

As a Data Leader/Delivery Manager at Sutherland, your key responsibilities will include providing program-level support for client development projects in Big Data and Data Warehousing. You'll guide clients on executing their enterprise data vision, recommend best practices for data quality and governance, and partner with stakeholders to develop future data architectures. Moreover, your role will involve leading cloud strategy development and overseeing the migration of databases to cloud platforms such as AWS and GCP.

To qualify for the Data Leader/Delivery Manager position at Sutherland, candidates should have 15+ years of IT experience in Big Data, Data Warehousing, and Data Architecture. Familiarity with RDBMS and platforms like Oracle, Teradata, and Snowflake is essential. Strong experience in data modeling, ETL management, and cloud infrastructure for enterprise data solutions is also required, along with a solid understanding of data governance regulations.

Successful candidates for the Data Leader/Delivery Manager role at Sutherland should have extensive experience in implementing large-scale data projects, including modernization and migration efforts. Proficiency in data normalization, metadata management, and source-to-target mapping is crucial. Additionally, hands-on experience with data quality projects and compliance with GDPR/CCPA regulations is highly beneficial.

At Sutherland, ensuring data quality and governance is a top priority for the Data Leader/Delivery Manager. You will be responsible for setting standards across multiple datasets and driving best practices throughout client enterprises. This involves collaborating with stakeholders to identify gaps in data quality, implementing strategies for data trust, and overseeing compliance with governance regulations to ensure consistent and reliable data management.

As a Data Leader/Delivery Manager at Sutherland, you'll have ample opportunities for growth and professional development. With the chance to work alongside leading industry experts on innovative projects, you can expand your knowledge in AI, cloud technologies, and data governance. Sutherland values continuous learning, so you'll have access to various training programs and resources to sharpen your skills and advance your career.

When answering this question, provide specific examples of projects where you have successfully created schemas and modeled data to meet business requirements. Discuss your approach to balancing complexity and performance, and highlight tools or methodologies you've used, such as Entity-Relationship diagrams or normalization techniques.

A strong response would include a breakdown of your experience with various migration strategies, such as 'lift and shift' versus rearchitecting. Detail how you assess the client's needs and plan for data integrity and minimal downtime during the migration process, ensuring all stakeholders are engaged and informed.

Discuss specific practices you have implemented to maintain data governance, such as regular audits, compliance checks, and the establishment of data stewardship teams. Emphasize the importance of cross-departmental collaboration and communication to keep data quality at the forefront of project management.

Highlight a particularly challenging big data project, explaining the obstacles faced and the strategies you implemented to overcome them. Focus on your problem-solving skills, adaptability, and any innovative solutions you devised to support successful project delivery.

Provide insights into the tools you have used, such as Tableau or Power BI, and explain why you prefer them. Discuss how you leverage these tools to translate complex data into actionable insights and how they facilitate communication with non-technical stakeholders.

Outline your approach to engaging with stakeholders, covering your strategies for effective communication, identifying stakeholder needs, and managing expectations. Highlight your experience in facilitating workshops and maintaining relationships throughout the project lifecycle.

Discuss your familiarity with cloud platforms, specifically AWS and GCP, and describe projects where you designed or migrated data architectures to these environments. Highlight the benefits you've observed, such as scalability and cost-effectiveness, as well as any challenges you've faced.

Share your methodologies for ensuring data quality throughout ETL processes, such as implementing validation rules, using data profiling, and conducting regular quality checks. Emphasize your commitment to providing accurate and meaningful data for business decision-making.

Comment on your familiarity with GDPR and how you have applied compliance measures in previous projects. Highlight specific initiatives you've led to ensure adherence, such as data mapping, consent management, and implementation of privacy policies.

Discuss your belief in the importance of collaboration in data projects, mentioning how you leverage cross-functional teams to share insights and achieve common goals. Provide examples where teamwork has led to innovative outcomes or prevented potential issues.