Data Delivery Manager

Job Title: Data Delivery Manager

Overview:
The Data Delivery Manager is responsible for managing and overseeing the end-to-end delivery of data solutions, from data architecture and ingestion to processing, analysis, and reporting. This role ensures that data projects are completed on time, within scope, and aligned with business objectives. The Data Delivery Manager works with cross-functional teams, including data engineers, analysts, and other stakeholders, to deliver high-quality data solutions.

Key Responsibilities:

1. Project and Program Management:

• Lead and manage the delivery of data-driven projects, ensuring they are completed on time and within budget.
• Develop and maintain project plans, timelines, and resource allocation.
• Monitor project progress and proactively identify risks, implementing solutions to ensure successful project completion.
• Ensure alignment between data initiatives and business goals, maintaining continuous communication with stakeholders.

2. Stakeholder Engagement:

• Serve as the primary point of contact between business stakeholders and the data team, translating business requirements into technical specifications.
• Collaborate with business leaders to understand data needs and develop solutions that meet those needs.
• Provide regular updates on project status, risks, and key deliverables to stakeholders and leadership teams.
• Facilitate meetings to gather requirements and communicate project milestones.

3. Data Strategy & Architecture:

• Oversee the design and implementation of data solutions that support business objectives.
• Ensure adherence to data governance and quality standards throughout the data pipeline lifecycle.
• Collaborate with data architects to define scalable, secure, and high-performance data architectures.
• Support data integration initiatives across different platforms, ensuring smooth and efficient data flow.

4. Team Leadership and Development:

• Manage cross-functional teams of data engineers, analysts, and other professionals to deliver projects effectively.
• Provide leadership and mentoring to team members, fostering a culture of collaboration, innovation, and continuous learning.
• Set clear expectations, performance goals, and career development opportunities for the team.
• Address and resolve any team challenges, ensuring high levels of productivity and motivation.

5. Quality Assurance:

• Ensure the accuracy, reliability, and quality of data solutions by implementing robust testing, validation, and review processes.
• Develop and enforce data standards, best practices, and methodologies to ensure consistent, high-quality deliverables.
• Drive continuous improvement initiatives, analyzing past projects and identifying areas for enhancement.

6. Risk Management and Troubleshooting:

• Identify potential risks to project delivery, including data pipeline issues, resource shortages, or technical blockers, and implement mitigation strategies.
• Troubleshoot and resolve data-related issues and challenges during the project lifecycle.

7. Reporting and Analytics:

• Oversee the creation and maintenance of data dashboards, reports, and performance metrics.
• Ensure that data solutions provide actionable insights for the business, driving informed decision-making.

Experience:

• 5+ years of experience in managing programs related to data management, data engineering, or analytics.
• Proven track record in managing data projects and delivering data solutions in a timely manner.
• Experience with data integration, data warehousing, and data modeling.
• Strong understanding of data pipeline management, ETL processes, and data analytics.

Skills:

• In-depth knowledge of data management tools and technologies (e.g., SQL, NoSQL, ETL tools, cloud platforms such as AWS, Google Cloud, or Azure).
• Proficient in project management methodologies (Agile, Scrum, Waterfall).
• Strong leadership and team management skills, with the ability to drive collaboration across different functions.
• Excellent communication skills with the ability to translate complex data-related concepts into understandable terms for non-technical stakeholders.
• Analytical mindset with strong problem-solving abilities.
• Knowledge of data visualization and reporting tools (e.g., Power BI, Tableau, Looker) is a plus.

Certifications:

• Project Management Professional (PMP) or Scrum Master certification (preferred).
• Data-related certifications (e.g., AWS Certified Big Data, Google Professional Data Engineer) are a plus.

Preferred Skills:

• Experience with big data technologies (e.g., Hadoop, Spark, Kafka).
• Familiarity with machine learning or AI applications related to data solutions.
• Experience with data governance and compliance (e.g., GDPR).