Data Engineer

Job Purpose

An established consumer-focused organisation is seeking a skilled Data Engineer to join its data and analytics function. This role is suited to someone passionate about big data and analytics, with the ability to translate complex datasets into meaningful insights that support business decision-making across multiple departments.

The successful candidate will be responsible for both recurring and ad hoc analytical deliverables while playing a key role in building and maintaining scalable, reliable data infrastructure. Working closely with cross-functional teams, you will ensure data availability, quality, and accessibility to enable advanced analytics and reporting.

Key Responsibilities / Competencies

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Collaborate with data scientists, analysts, and business stakeholders to gather and define data requirements
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Design, develop, and maintain robust data pipelines and ETL processes
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Implement and support data warehousing and storage solutions
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Optimise data pipelines for scalability, performance, and reliability
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Ensure high standards of data quality, validation, and governance
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Monitor, maintain, and troubleshoot data infrastructure
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Design systematic ETL and pipeline solutions aligned to business specifications
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Develop and deploy ETL processes in accordance with approved solution architecture
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Uphold data governance, compliance, and quality assurance standards
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Engage stakeholders in a professional, service-oriented manner
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Demonstrate effective self-management and strong teamwork capabilities
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Stay current with emerging technologies and best practices within data engineering

Minimum Qualifications & Experience

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Bachelor's degree in Computer Science, Information Technology, or a related discipline
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5-10 years' experience in data engineering within a professional environment
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Strong experience designing and developing data warehouses aligned to Kimball methodology
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Proven expertise in ETL design and development
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Proficiency in SQL and programming languages such as Python, Scala, or Java
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Experience with ETL tools, data integration, and orchestration frameworks
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Strong understanding of data modelling, database design, and storage architectures
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Experience with cloud-based data warehousing platforms (e.g., Snowflake, Redshift)
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Experience working with AWS environments
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Ability to ingest and process structured and semi-structured data (CSV, JSON, flat files, etc.)
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Understanding of data security and compliance best practices
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Strong problem-solving, troubleshooting, and communication skills
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Industry exposure within retail, financial services, or logistics environments advantageous
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Relevant certifications (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer) beneficial