Job Description

JOB OVERVIEW / ROLE PURPOSE
We are seeking a Senior Data Engineer with expertise in cloud data platforms, big data pipelines, and advanced analytics. In this role, you'll architect and maintain scalable, high-performance data ecosystems that power machine learning models, BI dashboards, and AI-driven decision-making.
You'll combine hands-on engineering with strategic leadership, mentoring junior engineers, guiding best practices, and collaborating with data scientists, software engineers, and business stakeholders. This role is ideal for someone who thrives in cloud-native environments (AWS preferred) and wants to make a real impact with data.
"cloud data platforms"
"big data pipelines"
"real-time and batch data"
"AI-driven decision-making"
"machine learning workflows"
"ETL / data ingestion"
"Power BI, Tableau"
"AWS data engineer jobs"
MINIMUM REUIREMENTS
Qualifications:

• Degree or diploma in Computer Science, Information Systems, Engineering, or a related field.
• AWS certifications or equivalent practical expertise.

Experience:

• 4 - 7 years of hands-on data engineering
• Experience leading or mentoring junior engineers.
• Advanced proficiency in Python and SQL.
• Strong experience with BI tools like Power BI for data storytelling.
• Strong database design knowledge and experience with data warehousing techniques and modelling approaches.
• Experience building and maintaining cloud-based data architecture (AWS preferred).
• Hands-on experience with data ingestion from, amongst others: Microsoft SQL Server, Oracle, MongoDB, Amazon S3 and other AWS data services, HTTP APIs, SFTP, and various file systems.
• Proficiency with Git, CI/CD pipelines, and Agile methodologies.
• Hands-on designing and development of complex data pipelines from multiple sources into a central data platform/lakehouse.
• Familiarity with machine learning workflows and supporting analytics teams.
• Strong problem-solving, analytical, and communication skills
• Ability to work independently and take initiative on projects
• Business acumen and ability to translate technical work into business impact

WHAT YOU WILL DO!
Data Engineering & Pipeline Development

• Design, build, and optimize cloud-native, big data pipelines (AWS, Python, SQL).
• Develop real-time and batch data pipelines for analytics and AI/ML applications.
• Ensure data quality, scalability, and governance across all pipelines.

Data Platform Design & Architecture

• Contribute to the architecture of cloud data platforms, data lakes, and lakehouses.
• Implement automation, monitoring, and CI/CD pipelines for modern data workflows.
• Integrate data from multiple structured and unstructured sources (SQL Server, Oracle, MongoDB, APIs, AWS S3, file systems).

Leadership & Mentorship

• Lead by example -- provide technical mentorship to junior engineers.
• Champion best practices in data engineering, testing, and DevOps.
• Conduct code reviews and encourage knowledge sharing.

Collaboration & Business Impact

• Partner with data scientists, BI analysts, and business teams to deliver actionable insights.
• Translate complex business requirements into technical solutions.
• Develop and maintain data products, self-service analytics, and BI dashboards (Power BI preferred).

Continuous Innovation

• Stay ahead of the curve on AI, machine learning workflows, and modern data tools.
• Explore opportunities to implement new technologies in big data, real-time streaming, and cloud data services.
• Drive a data-first culture across the organisation.

Skills Required