Senior Data Engineer

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.

Required Qualifications

• 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