Head of Data Engineering

The Head of Data Engineering is primarily responsible for leading the data engineering team, overseeing the development, deployment, and maintenance of scalable data infrastructures and pipelines. The Head of Data Engineering will be responsible for the execution of the overall Data strategy for Digital transformation. They will work closely with the business, digital, and IT teams to develop the data architecture to enable the digital and AI/ML use cases. The Head of Data Engineering also drives the team’s data engineering practices and acts as a coach for data engineers on the use-cases and create a best-in-class engineering capability.

KEY ACCOUNTABILITIES:

• Execution and implementation of the data management strategy
• Design overall data architecture with best-in-class concepts and technologies in mind
• Guide project teams on data strategy related to coding practices, data engineering, and analytical modelling
• Coach team in coding to develop robust data pipelines and architecture solutions
• Advocate and educate on the value of data driven decision making focusing on the “how and why” of solving problems
• Work with Product Owner to align the roadmap with strengths and opportunities within the data architecture
• Evolve data engineering solutions continuously and challenge the status quo
• Execute organisation vision of Industry 4.0 by developing and implementing short-term and long-term data strategies.
• Develop the long-term data roadmap in collaboration with IT teams around platform selection and usage
• Provide the team with a roadmap for implementing data engineering best practices ▪ build data engineering capability by providing technical leadership and career development for the organisation
• Lead, mentor, collaborate and coach a growing team of Data Engineers fostering a culture of innovation and agility.
• Devise talent strategy for the team – identify resource gaps or inefficiencies, build hiring plan, recommend promotions and manage performance for consistency with the needs and vision of the department.

AUTHORITY/ DECISION MAKING:

• Overall implementation of data infrastructure for scalability and performance.
• Oversee hiring, training, and resource allocation for the team.
• Prioritise data engineering projects based on business needs.
• Manage and allocate the department’s budget.
• Set and enforce data quality standards and compliance.
• Align data initiatives with other department heads.
• Address and resolve major challenges faced by the team.
• Decide on third-party vendor partnerships.
• Drive the long-term vision for data engineering in the company.

QUALIFICATIONS & SKILLS:

• Bachelors degree required, MS or PhD preferred
• Bachelors in Data Science, Computer Science, Engineering, Statistics and 10+ years of relevant experience.
• Minimum 10+ years of managerial experience utilizing strong leadership skills, including mentoring, communication, decision-making, and project management.
• Knowledge of the Big Data technology landscape beyond the buzzwords; Experience with big data and analytics programming languages such as Python, R, Spark, NoSQL
• Experience with batch and real-time processing frameworks (Hadoop, Apache Storm, Apache Kafka, Apache Spark etc.)
• Proficiency working with DataFrames and writing complex SQL queries
• Familiar with production Cloud / DevOps environments and Data lake, Data transformation, ETL/ELT, and other data concepts
• Experience of leveraging MS/Azure ecosystem to manage the development and maintenance of cloud platform operations
• A broad set of technical skills and knowledge across hardware, software, systems and solutions development
• A proven track record of using quantitative analysis to impact key business or product decisions
• Solid grasp of and experience with implementing and operating software development methodologies
• A solid grasp of common statistical applications and methods (A/B tests and multivariate experiments, probabilities, regression)
• Understanding of Agile Software Development Lifecycle and project planning/execution skills

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