Data Engineering Practice Lead at NTT Ltd.

• The Director, Data Engineering is a leadership role accountable for operationally managing a Data Engineering Team.
• The Data Engineering Practice lead will lead the design, development of the enterprise data platform and pipelines. 
• This role is further responsible for overseeing SAP data migrations, ensuring seamless integration and transformation of legacy systems into modern cloud-based architectures. 
• The person will drive innovation, scalability, and governance in data engineering practices while managing a high-performing team.

Key Responsibilities:

• Manages a team of Managers and Data Engineers to ensure achievement of team objectives/KPIs and through continuous coaching and mentoring helps the team to understand and apply data to solve business solutions.
• Develop the new Data Platform - Execute the data engineering strategy per the selected platform.
• SAP Data Migration - Lead end-to-end SAP data migration projects, including planning, mapping, transformation, and validation.
• Engineering Team Leadership - Build and manage a team of data engineers and technical leads. Foster a culture of innovation, collaboration, and continuous improvement.
• Data Pipeline Development - Oversee development of robust ETL/ELT pipelines using Azure Data Factory, Databricks, Snowflake Streams/Tasks, and SAP tools. Ensure pipelines are optimized for performance, reliability, and cost-efficiency.
• Data Management - partner with data management practice lead and governance lead to ensure adherence to data quality, lineage, and security standards. Implement monitoring and alerting for data pipeline health and SLA compliance.
• Stakeholder Engagement - Collaborate with business units and the internal analytics teams and IT to align data engineering efforts with strategic goals. Translate business requirements into scalable technical solutions.
• Ensure industry standards best practices are applied to development activities and continuously ensures the team remains abreast of latest technology and tools in the area of data engineering.
• Works across multiple areas on data set to ensure solutions are successfully executed, within agreed upon time frames.

Knowledge and Attributes:

• Excellent ability to thrive in a dynamic, fast-paced environment.
• Strong quantitative and qualitative analysis skills.
• Strong desire to acquire more knowledge to keep up to speed with the ever-evolving field of data science.
• Strong curiosity to sift through data to find answers and more insights.
• Excellent understanding of the information technology industry within a matrixed organization and the typical business problems such organizations face.
• Excellent ability to translate technical findings clearly and fluently to non-technical team business stakeholders to enable informed decision-making.
• Excellent ability to create a storyline around the data to make it easy to interpret and understand.
• Self-driven and able to work independently yet acts as a team player.
• Excellent ability to apply data science principles through a business lens.
• Strong desire to create strategies and solutions that challenge and expand the thinking of peers and senior leadership teams.
• Excellent ability to think strategically about how to use data to drive competitive advantages.
• Excellent management and leadership skills.

Academic Qualifications and Certifications:

• Bachelor’s degree or equivalent in Data Science, Business Analytics, Mathematics, Economics, Engineering, Computer Science or a related field.
• Relevant programming certification preferred.
• Agile certification preferred.

Required experience:

• Significant demonstrable experience with one or more programming languages, statistical packages and database languages.
• Significant demonstrable experience with data warehouse and data lake technical architectures, infrastructure components, ETL/ ELT, and reporting/analytic tools.
• Significant demonstrable experience applying statistical methods to solve business problems.
• Significant demonstrated experience with distributed data platform tools such as MS Azure, SAP Snowflake, Spark, MySQL, etc.
• Significant demonstrated experience in working in micro-services architecture working with APIs development.
• Significant demonstrable experience of full-stack software development with prolific coding abilities.
• Significant demonstrated experience with Agile Development Methodologies and Test-Driven Development.
• Solid line manager experience leading and managing a team of Data Engineering Teams