Job Description

Role title:

Specialist - Data Engineer

Location: Bryanston


Duration: 12 months (Hybrid)

Role purpose:

o Data Pipeline Development: Developing scalable and efficient data pipelines as per business requirements.


o Collaboration & Stakeholder Engagement: Collaborating with functional data owners in solving data related queries and provide the necessary support for data driven initiatives.


o Infrastructure & Governance: Managing data integrity, security, quality and accessibility.


o Reporting Solutions: Assist with development of reporting solutions.

Core competencies, knowledge and experience

o Experience with analysing data.


o In-depth knowledge and practical experience of data lifecycle management.


o Experience working with cross-functional teams and engaging with business stakeholders.


o Ability to manage multiple priorities independently.


o Strong communication and presentation skills.

Must have technical / professional qualifications

:


o 3-5 years of experience in data engineering or a similar role.


o Proficiency in SQL and Python.


o Experience with data pipeline tools (e.g., Apache Airflow, dbt).


o Hands-on experience with cloud platforms (AWS, Azure).


o Strong knowledge of data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).


o Familiarity with containerization tools (Docker, Kubernetes) is a plus.


o Experience in developing reporting solutions using visualization tools (e.g. Power BI).


o Desirable experience with real-time data processing frameworks (e.g., Kafka, Spark Streaming).


o Experience with Smartsheet's is a plus.

Key performance indicators

o Data Pipeline Efficiency & Uptime - Measure the reliability and performance of ETL (Extract, Transform, Load) or ELT workflows, ensuring minimal downtime and efficient data processing.


o Data Quality & Accuracy - Track metrics like data completeness, consistency, and error rates to ensure high-quality, reliable datasets for analytics and decision-making.


o Scalability & Optimization - Evaluate improvements in data infrastructure, including query