Requirements

Key Responsibilities

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  Design, build and optimise enterprise data pipelines and data platforms.
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  Develop scalable cloud-native data engineering solutions.
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  Collaborate with business and technical stakeholders to deliver data-driven solutions.
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  Define and maintain data architecture and engineering standards.
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  Drive DevSecOps and CI/CD best practices.
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  Mentor and coach Data Engineers.
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  Ensure data quality, governance and platform reliability.
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  Participate in Agile ceremonies and technical planning.
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  Drive continuous improvement and innovation across the data environment.

Requirements

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  Bachelor's Degree or Diploma in Computer Science, Engineering, Mathematics, Information Systems or similar.
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  8+ years' experience in Data Engineering or Software Engineering.
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  Strong experience with Business Intelligence and Data Warehousing.
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  Advanced SQL skills.
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  Expert knowledge of Python and PySpark.
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  Experience with Hadoop and Apache Spark.
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  Strong AWS experience, including EMR, S3, Athena, RDS, Lambda and API Gateway.
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  Good understanding of SDLC, Solution Architecture and DevSecOps.
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  Experience with Azure, Google Cloud Platform and Snowflake is advantageous.
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  Previous experience leading or mentoring engineering teams.
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  Retail or FMCG industry experience is essential.

Technical Skills

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  Python
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  PySpark
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  SQL
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  AWS
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  Hadoop
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  Apache Spark
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  Data Warehousing
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  Business Intelligence
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  ETL / ELT
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  Snowflake
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  Azure
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  Google Cloud Platform
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  DevSecOps
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  CI/CD
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  Solution Architecture