Core Identity and Role

Position Overview: A senior data engineering role responsible for leading data strategy, architecture, and platform design aligned with business needs.
Operational Focus: Drives scalable, secure, and high-performing data solutions to support analytics, AI, and enterprise data initiatives.
Work Environment: Operates in complex environments, guiding both new (greenfield) and existing (brownfield) implementations from concept to delivery.
Stakeholder Interaction: Collaborates with cross-functional teams, including data stewards and agencies, while influencing adoption of modern engineering practices and standards.

Key Technical Functions

Data Strategy & Architecture:
Lead and implement data engineering strategies and architecture blueprints; evaluate platforms and solutions to meet evolving data needs.
Data Solution Design:
Translate business requirements into scalable technical specifications and architect end-to-end data solutions.
Data Pipeline Engineering:
Design and build robust ingestion pipelines to collect, clean, integrate, and harmonize data from multiple sources.
Cloud Infrastructure & Security:
Develop secure, cloud-based data infrastructure and access mechanisms across platforms such as AWS, Azure, or GCP.
ETL Optimization & Performance:
Monitor and optimize ETL processes and databases for reliability, scalability, and efficiency.
Data Modelling & Governance:
Create reusable data models, maintain data catalogues, and enforce governance, quality, and security standards in collaboration with stakeholders.
Implementation & Advisory:
Guide implementation efforts across project lifecycles and develop standardized approaches for discovery, assessment, and solutioning.
Engineering Leadership:
Promote engineering excellence, mentor team members, and drive adoption of modern data and infrastructure practices.

Education:
Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or related disciplines.
Experience:
5–10 years in data engineering, cloud infrastructure, or platform engineering.
Technical Skills:
- Strong foundation in data system design, data structures, algorithms, and architecture modelling
- Hands-on experience with cloud platforms (AWS, Azure, GCP) and distributed technologies (Spark, Hadoop)
- Proficiency in Python and SQL
- Experience with orchestration tools (Airflow, Azure Data Factory) and DevOps tools (Docker, Git, Terraform)
- Familiarity with CI/CD pipelines and infrastructure-as-code practices
- Experience with platforms such as Databricks, Snowflake, or Denodo and building batch/real-time pipelines
- Strong knowledge of data governance, security, and privacy
Professional Skills:
- Excellent communication and stakeholder management abilities
- Proven capability to mentor and develop technical talent