Purpose of the role
The purpose of the AVP Senior Data Engineer role is to provide strategic leadership in data engineering, overseeing the development and maintenance of data infrastructure, and ensuring the availability, reliability, and performance of data solutions. This position plays a critical role in supporting data-driven decision-making across the organization
Scope of the role
• Leading the data engineering team and providing technical guidance.
• Architecting and optimizing data storage solutions, including data warehouses and data lakes.
• Designing data models and overseeing data integration and transformation efforts.
• Monitoring and optimizing data infrastructure performance.
• Managing and mentoring a team of data engineers.
• Collaborating with cross-functional teams to fulfil data requirements.
• Ensuring data security, privacy, and compliance with regulations.
Key Responsibilities
• Providing strategic direction and technical leadership in data engineering.
• Leading the design, development, and deployment of ETL processes and data pipelines.
• Integrating data from various sources and transforming it for analytics.
• Maintaining data quality and implementing data governance best practices.
• Managing and mentoring a team of data engineers for professional growth.
• Collaborating with stakeholders to understand and fulfil data requirements.
• Documenting data processes, architectures, and best practices.
Foundational Competencies
• Strong leadership and team management skills.
• Excellent problem-solving and communication skills.
Functional Competencies
• Proficiency in programming languages such as Java, or Scala, SQL, Python.
• Extensive experience with ETL tools, data integration, and data transformation.
• In-depth knowledge of data storage technologies (relational databases, NoSQL, distributed file systems).
• Expertise in data modelling, database design and data warehousing.
• Familiarity with data governance, security, and compliance standards.
• Experience with big data technologies (e.g., Hadoop, Spark, Hive, Azure, Databricks) is a plus.
• Experience in container orchestration framework like Kubernetes is a plus.
• Experience in Infrastructure as Code and DevOps, MLOps and DataOps is a plus.
Experience
10+ years of proven experience in data engineering, with a focus on building and maintaining data pipelines and data warehouses
Qualifications
• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
• Relevant certifications in data engineering and Cloud computing are advantageous.
