Head Data Engineering

Data Strategy and Planning

• Develop and execute a comprehensive data engineering strategy aligned with the organization's goals and objectives.
• Collaborate with senior leadership to identify business requirements and prioritize data initiatives accordingly.

Leadership and Team Development

• Foster a culture of continuous learning and development, providing opportunities for team members to enhance their skills.
• Identify skill gaps within the data engineering team and arrange training programs to address them.
• Mentor and coach team members to facilitate their career growth within the organization.
• Set clear goals and objectives for the data engineering team and monitor progress.
• Encourage knowledge sharing and collaboration within the team to strengthen their expertise.

Data Integration & ETL Development

• Oversee the development and maintenance of ETL (Extract, Transform, Load) processes to ingest and transform data from various sources.
• Define and enforce ETL best practices, coding standards, and documentation guidelines for the data engineering team.
• Conduct code reviews and provide feedback to maintain high-quality ETL code.
• Establish and maintain data quality checks and validation processes within ETL workflows to ensure data accuracy and consistency.
• Collaborate with data scientists and analysts to ensure data availability and quality for analytics and reporting

Reporting & Data Visualization

• Oversee the Reports and Dashboards development that fulfill the Regulatory requirements as well as facilitate data-driven decision-making at all levels of the organization.
• Promote best practices in data visualization to ensure that insights are effectively communicated to non-technical stakeholders.

API Development

• Lead the design and development of data APIs that enable secure and efficient access to organization's data assets.
• Collaborate with data engineers and software developers to define API specifications, endpoints, and authentication mechanisms.
• Ensure that data APIs are well-documented and adhere to best practices for RESTful API design.

Conduct POTs & Recommend Technology Improvements

• Stay current with data engineering technologies and trends, recommending and implementing tools and frameworks that improve efficiency and performance.
• Lead the identification and execution of Proof of Technology (PoTs) and pilot projects to evaluate emerging data technologies and methodologies.
• Collaborate with data engineers and data scientists to design and execute PoTs that address specific business challenges or opportunities.
• Assess the feasibility, performance, and scalability of new data-related tools, frameworks, and platforms through experimentation.
• Provide recommendations based on PoT results, enabling informed decisions regarding technology adoption and integration.

Minimum qualifications:

• Bachelor’s or Master’s degrees in computer science / data engineering or related fields

Minimum experience: 

• Minimum 5 years of experience as either a Development Head or Data Architect or Solution Architect
• Proficiency in data warehousing, ETL processes, and database technologies.
• Strong knowledge of data modeling and database design principles.
• Familiarity with data governance, security, and compliance standards.
• Expertise in programming languages (e.g., Python, Java, SQL) and data engineering tools (e.g., Informatica, Apache Spark, Impala and Hadoop).
• Excellent communication and leadership skills.
• Problem-solving and critical-thinking abilities.