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AWS Cloud Data Engineer



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.


Required Skill Profession

Other General



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