Data Engineer

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Data Pipeline Development
Data Engineers design and develop data pipelines to extract, transform, and load (ETL) data from various sources into a data warehouse, data lake, or data mart. They use technologies such as Apache Spark, Apache Kafka, or equivalent to handle data ingestion and processing.

Database Management
They have expertise in working with different types of databases, both relational and non-relational. This includes SQL databases like SQL Server, Oracle, MySQL, as well as NoSQL databases like CosmosDB, Cassandra, or Redis. They optimize database performance, ensure data integrity, and implement database security measures.

Data Modeling
Data Engineers are skilled in designing and implementing data models that support efficient data retrieval, storage, and analysis. They work with stakeholders to understand data requirements and create effective data schemas.

Big Data Technologies
They are familiar with big data technologies such as Apache Hadoop, Apache Hive, or Apache HBase. Data Engineers leverage these technologies to handle and process large volumes of data efficiently, utilizing distributed computing frameworks like Apache Spark or MapReduce.

Data Transformation and Integration
Data Engineers perform data transformation tasks to ensure data consistency and quality. They use tools like SQL, Python, or ETL tools (e.g., SSIS, Talend) to cleanse, transform, and merge data from multiple sources.

Cloud Technologies
They have experience working with cloud platforms like AWS, Azure, or Google Cloud Platform. Data Engineers leverage cloud services and infrastructure to build scalable and cost-effective data solutions. This includes utilizing cloud-based storage, computing, and data processing services.

Programming and Scripting
Data Engineers are proficient in programming languages like Python SQL or Scala. They write code to automate data workflows, develop data pipelines, and perform data manipulation tasks. They also utilize scripting languages like Shell scripting for automation purposes.

Data Quality and Governance
Data Engineers implement data quality frameworks and processes to ensure data accuracy, completeness, and consistency. They collaborate with data stewards and data owners to establish and enforce data quality standards.

Data Warehousing and Business Intelligence (BI)
They work with data warehousing and BI tools like SQL-based databases, OLAP cubes, or reporting tools (e.g., Tableau, Power BI) to enable data analysis and visualization for end-users.

Collaboration and Communication
Data Engineers collaborate with cross-functional teams, including data scientists, data analysts, and business stakeholders. They communicate effectively to understand data requirements and provide technical solutions to meet business needs.

• Please note we will apply relevance to our Talent Management and Talent Development Programme as part of our recruitment process.
• Shortlisted candidates may need to complete an assessment.

This position requires trust and honesty it has access to customers financial details - therefore a credit and criminal record check will be conducted. The qualifications identified herein are an inherent job requirement; therefore, a qualification verification check will be done. By applying for this role, and supplying the necessary details, you hereby grant us permission to apply for these checks. This will be done in a confidential manner, and solely for the purposes of verification.

Should you not hear from us within 2 weeks, please deem your application as unsuccessful.

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