Data Engineer (On-Site) at Aspen Pharma Group

Objective:

The Data Engineer will play a crucial role in designing, building, and maintaining our data infrastructure and systems. The Data Engineer will be responsible for understanding business requirements, knowledge of current and future state architecture on data platform design and business capabilities, knowledge of enterprise data standards and deep data expertise in data modeling, ETL Processes, database management and data integration to design data architecture solutions that can be implemented in a cost-effective manner while ensuring data quality, reliability, and security.  

KEY RESPONSIBILITIES

Data Infrastructure Design and Development:

• Design, develop, and maintain scalable and cost-effective data infrastructure on Azure cloud, considering budgeting techniques, to support data processing, storage, and analysis.
• Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions that align with budgetary constraints.
• Implement best practices for data engineering, including data modelling, schema design, and performance optimization while optimising costs.

Data Integration and ETL:

• Develop and implement robust Extract, Transform, Load (ETL) processes to integrate data from various sources into the data infrastructure.
• Ensure data integrity, accuracy, and consistency throughout the ETL pipeline.
• Monitor and troubleshoot data integration processes to identify and resolve any issues or anomalies.

Database Management and Optimization:

• Administer and manage databases on Azure SQL Database, implementing cost-effective database management techniques such as resource utilization optimization and query optimization.
• Ensure data security, privacy, and compliance with relevant regulations.
• Implement and maintain backup, recovery, and disaster recovery strategies for critical data assets.

Data Quality and Governance:

• Develop and implement data quality frameworks, processes, and standards.
• Collaborate with data scientists, analysts, and business stakeholders to define data quality metrics and monitor data quality over time.
• Work with the data governance team to ensure compliance with data governance policies and procedures.

Azure Cloud Services:

• Leverage Azure cloud services to build scalable and cost-effective data solutions.
• Implement data pipelines using Azure Data Factory or SSIS.
• Utilize Azure security features and practices to ensure data protection and compliance.

Collaboration and Documentation:

• Collaborate with cross-functional teams, including business, analysts, and software engineers, to understand data requirements and deliver optimal data solutions.
• Document data engineering processes, system architecture, and technical specifications.
• Provide technical guidance and mentorship to junior data engineers or analysts as needed.

Requirements

SKILLS AND ATTRIBUTES

• Quick learner and self-starter with superior problem-solving abilities and time management skills.
• Strong organizational skills and ability to multi-task in a past-paced, dynamic environment.
• Excellent problem-solving, analytical, and communication skills.
• Ability to work collaboratively in a cross-functional team environment.
• Strong interpersonal and entrepreneurial skills to allow for mutual understanding of business needs and development of cooperative solutions.
• In-depth knowledge of data modelling, data warehousing, and ETL processes.
• Attention to detail.
• Responsibility and Accountability.
• Innovation.
• Flexibility and tolerance for ambiguity.

KNOWLEDGE

• Extensive knowledge of SQL and Azure Cloud Services
• Advanced knowledge of Microsoft Office products, PowerPoint and Word and a master level of knowledge in Excel
• Strong programming skills in languages such as SQL, Python, or similar
• Extensive knowledge of Master Data Governance
• Knowledge of business applications and related tools, for example, SAP, Supply Chain applications, advantageous
• Knowledge of data governance principles and compliance regulations
• System analysis and design
• Data Science

EDUCATION & EXPERIENCE

• Matric
• Minimum qualification: Bachelor’s Degree in Computer Science, Data Informatics, Information Technology, or any other related degree
• 5+ year SQL experience
• 3-5 years’ experience in Pharmaceutical/Life Sciences industry
• Experience working with and understanding SAP data.
• Experience with BI tools supporting the ETL process/data integration and visualisation e.g., SSIS/SQL/Qlik/Tableau/Power BI
• Supply Chain experience