Peter Olomolaiye

• · Monetization of usage telemetry data driving up to 3% MOM usage increase and over 10% YOY revenue increase.
• · Drive cross-functional collaboration as a key member of agile teams, working closely with data scientists, software engineers, and product managers to design, develop, and implement data-driven solutions that deliver better service to our customers.
• · Build pipelines processing petabytes of data monthly.
• · Lead and mentor a team of data engineers, fostering a collaborative and high-performing culture that promotes innovation, knowledge sharing, and continuous learning.
• · Collaborate with data scientists to develop new actionable insights that improve customer experience for Microsoft's clients, leveraging their domain expertise and translating it into scalable data solutions.
• · Collect consented telemetry data on product usage and facilitate its availability for decision-making through collaborative efforts, utilizing tools like SQL, Cosmos, Kusto, Azure ML, R, Python, Spark, and Hadoop.
• · Champion effective communication and stakeholder management, ensuring alignment of data initiatives with business goals and fostering strong relationships with cross-functional teams and senior leadership.
• · Actively participate in knowledge-sharing forums, presenting findings, best practices, and innovative ideas to encourage a culture of collaboration and continuous improvement.

• Pioneered the establishment of the data office and assumed leadership.
• Implemented an on-premise SQL server data warehouse, empowering the organization with robust data insights for informed decision-making.
• Directed a team of data engineers in developing seamless data pipelines, integrating and transforming diverse data sources to ensure high-quality data availability.
• Deployed automation solutions for data processes, reducing delivery and reporting time from over 3 days to under 15 minutes. This optimization allowed teams to focus more on strategic initiatives, leading to improved outcomes.
• Provided leadership and mentorship to the data engineering team, fostering a culture of excellence, collaboration, and continuous improvement.
• Ensured data quality, accuracy, and availability through rigorous data governance measures, regular audits, and establishment of best practices.
• Collaborated with stakeholders across the organization, including business leaders and analysts, to understand their data requirements and deliver analytics initiatives driving actionable insights and informed decision-making.

• Conceptualized, developed, and executed a fraud detection and prevention solution, resulting in savings equivalent to $300,000 (2019 Exchange rate) within a month post-deployment.
• Established and maintained a cloud-based data warehouse infrastructure(Azure).
• Directed a high-performing team of data engineers, overseeing data mining, development, visualization, and presentation to support management decision-making.
• Implemented robust data governance frameworks and ensured adherence to governance policies, guaranteeing data accuracy, reliability, and availability.
• Leveraged tools including Power BI, SSAS, SSIS, SQL, Azure ML, Azure Data Factory, Knime, and Python to deliver actionable business insights and foster a data-driven culture shift within the organization.

The Graduate/Management Associate Program is an accelerated career progression program put in place to develop identified talents for leadership. Individuals who have demonstrated the required traits are put through a rigorous selection process before being accepted into the program. Associates are rotated to different business units during their program to gain objective view of the organization and understand the various aspects of banking. My time on the program was as below.

• Graduate Associate (Technology and People)m Mar 2016 - Dec 2016 (9 Months)
• Graduate Associate (Corporate and Retail Sales) Jan 2017 - Dec 2017 (1 Year)
• Graduate Associate (Data) Jan 2018 - Jun 2018 (6 months)

My progression on the program took me through understanding and impacting the Technology # the Processes # the People # the Business # the Data