Current Jobs at Praesignis

Job Description

• We are seeking an experienced Senior Data Engineer to design, build and maintain scalable data pipelines and cloud-based data solutions. The successful candidate will play a key role in developing robust ETL processes, optimising data workflows and enabling data-driven decision-making across the organisation.

Key Responsibilities

• Design, develop and maintain scalable data pipelines and ETL processes.
• Build and manage cloud-based data solutions within AWS environments.
• Develop and optimise data integration workflows using AWS services and orchestration tools.
• Ensure data quality, reliability, security and governance across data platforms.
• Collaborate with data analysts, data scientists, architects and business stakeholders to understand data requirements.
• Monitor, troubleshoot and optimise data pipelines for performance and scalability.
• Implement best practices for data engineering, automation and DevOps processes.
• Support data warehousing and analytics initiatives.

Preferred Experience

• 5+ years of Data Engineering experience.
• Experience working in cloud-native AWS environments.
• Proven track record of delivering enterprise-scale data integration and ETL solutions.

Required Skills & Experience

• Proven experience as a Data Engineer or Senior Data Engineer.
• Strong hands-on experience with AWS cloud services.
• Experience developing and managing ETL/ELT pipelines.
• Strong experience with AWS Glue.
• Experience with Apache Airflow for workflow orchestration and scheduling.
• Proficiency in SQL and data modelling concepts.
• Experience working with large-scale datasets and distributed data processing frameworks.
• Strong understanding of data architecture and data integration principles.
• Experience with version control and CI/CD practices.

Advantageous Skills

• Experience with dbt (Data Build Tool).
• Experience with modern data warehouse technologies.
• Exposure to data lake architectures.
• Knowledge of Python or other programming languages is used in data engineering.
• Experience with Agile development methodologies.

Qualifications

• Bachelor's Degree in Computer Science, Information Systems, Engineering, or a related field.
• Relevant AWS certifications would be advantageous.

Key Competencies

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently and within cross-functional teams.
• Strong attention to detail and commitment to delivering high-quality solutions.
• Ability to manage multiple priorities in a fast-paced environment.
   

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Job Description

• The Data Engineer will design, develop and maintain scalable data solutions that support the organisation's data and analytics strategy. The role focuses on building reliable data pipelines, maintaining a Single Source of Truth (SSOT) data platform, improving data quality and enabling Power BI reporting through curated, analytics-ready datasets. The successful candidate will leverage Microsoft Fabric and Azure technologies to deliver secure, efficient and cloud-based data solutions.

Key Responsibilities

Data Engineering & Integration

• Design, develop and maintain data pipelines integrating data from multiple source systems.
• Build and optimise ETL/ELT processes and automated data ingestion workflows.
• Monitor and support data integration processes.

Datamart & Data Quality

• Support the development of the SSOT Datamart.
• Develop dimensional data models aligned to reporting requirements.
• Implement data quality, validation and standardisation processes.

Cloud & Analytics Enablement

• Develop solutions using Microsoft Fabric and Azure data services.
• Support migration of data assets to cloud platforms.
• Prepare and optimise datasets for Power BI reporting and analytics.

Collaboration & Delivery

• Work with business, Data Governance and BI teams to deliver data solutions.
• Translate business requirements into technical solutions.
• Contribute to Agile delivery and Azure DevOps practices.

Required Skills

• Microsoft Fabric and Azure Data Services.
• SQL, ETL/ELT development and data integration.
• Data warehousing and dimensional modelling.
• Power BI datasets and semantic models.
• Azure DevOps, Git and CI/CD.

Performance Criteria

• Reliable and automated data pipelines.
• Timely delivery of data integration and transformation components.
• Successful delivery of SSOT Datamart capabilities.
• High-quality datasets optimised for Power BI.
• Improved data quality and reduced manual effort.