Data Engineer

SUMMARY:
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POSITION INFO:

The Data Engineer will be responsible for designing, building, and optimising data pipelines and ensuring the efficient movement and transformation of data across various systems. The ideal candidate will have expertise in SQL, data modelling, and experience with cloud-based or on-premises data solutions. Additionally, knowledge of ML and statistical methodologies is beneficial for supporting advanced analytics.

Key Responsibilities:

• Develop, maintain, and optimise data pipelines for structured and unstructured data.
• Design and implement scalable and efficient data models to support analytical and operational reporting.
• Ensure data integrity, accuracy, and performance through best practices in database management.
• Work closely with data analysts, data scientists, and business stakeholders to understand data requirements.
• Implement ETL/ELT processes for data ingestion, transformation, and storage.
• Optimise database performance, including query tuning and indexing strategies.
• Monitor and troubleshoot data pipeline issues to ensure reliability and efficiency.
• Stay up to date with industry best practices and emerging data technologies.

Requirements:

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• 5+ years of experience in data engineering, database management, or a related role.
• Strong proficiency in SQL, including complex queries, indexing, and performance tuning.
• Expertise in data modelling and schema design for relational and NoSQL databases.
• Experience with data integration tools and ETL/ELT processes.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Strong understanding of the principles of data governance and security.

Preferred Skills & Experience:

• Exposure to big data technologies such as Spark, Hadoop, or Snowflake.
• Knowledge of Python or other scripting languages for data processing.
• Background in ML and statistics to support data science initiatives.
• Experience with CI/CD practices for data pipeline deployment.
• Proficiency in working with APIs for data extraction and integration.

Key Competencies:

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Ability to manage multiple projects in a fast-paced environment.
• Attention to detail and a focus on data quality.

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