NTT Group

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The Data Engineer is responsible for the transformation of data into a structured format that can be easily analysed in a query or report. The role is responsible for developing structured data sets that can be reused or compliment other data sets and reports. The individual analyses the data sources and data structure and will design and develop data models to support the analytics requirements of the business which includes management / operational / predictive / data science capabilities.

Working at NTT

Data Engineering

• The key responsibilities of an Azure data engineer include designing and implementing data storage solutions
• Building and maintaining data pipelines, ensuring data quality and accuracy, optimizing data processing performance, developing, and maintaining data models and schemas,
• Collaborating with other teams to provide data for analytics and reporting, and ensuring compliance with data security & privacy regulations.

Designing and implementing data storage solutions on Azure

• The data engineer is to design and implement data storage solutions on Azure. That includes selecting the appropriate Azure data storage services for the specific use case, such as Azure SQL Database, Azure Cosmos DB.

Building and maintaining data pipelines for data integration and processing

• Build and maintain data pipelines for data integration and processing. Accordingly, data is collected from various sources structured and unstructured data, files into blob storage.
• The data is transformed into a practical format and loaded into the appropriate data storage solution on Azure using tools such as Azure Data Factory.
• Ensure data is pushed in to SQL tables views, measures and relationship are manged in these tables.
• Must also ensure the data pipeline is scalable and efficient.

Ensuring data quality and accuracy through testing and validation

• Data quality and accuracy are critical to the success of any data management system.
• As a data engineer, you must ensure that the data stored and processed and is highly accurate. It involves testing and verifying the data at different phases of the data pipeline, from extraction through loading.

Optimizing data processing performance through tuning and monitoring:

• Data processing performance is another critical aspect of data engineering.
• The data engineer must ensure the data processing is efficient and scalable by tuning the data pipeline and monitoring performance.
• That involves identifying and resolving bottlenecks in the data pipeline and optimising the data processing algorithms.

Developing and maintaining data models and schemas:

• Data modelling and schema design are important aspects of data engineering.
• The data engineer must develop and maintain data models and schemas optimized for the specific use case. That involves selecting the appropriate data modelling techniques and ensuring the data schema is scalable and efficient.

Collaborating with other teams to provide data for analytics and reporting:

• As a data engineer, you will work closely with other teams, such as data analysts, data scientists, and software developers, to provide the data they need to perform their job functions.
• That involves understanding the specific data requirements of each team and ensuring that the data is available in the appropriate format.

Ensuring data security and privacy prerequisites are followed:

• The security and privacy of knowledge are important elements of any information management system.
• The data engineer oversees ensuring that the data stored and processed on Azure conforms with applicable data security and privacy requirements, such as POPIA and GDPR.

Technologies :

• SQL, Apache Spark, Azure Blob Storage, Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Azure Event Hubs, Azure Pipelines, Azure Repos, Azure SQL Database, Azure Stream Analytics, Azure Synapse Analytics, Microsoft Azure, Microsoft Power BI, PySpark, Python etc.

Skills Summary

Big Data Solutions, Business Analysis, Data Analysis, Data Analytics, DATABASICS, Data Lake, Data Modeling, Unstructured Data

What will make you a good fit for the role?

Workplace type:

Hybrid Working

Equal Opportunity Employer

NTT is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, color, sex, religion, national origin, disability, pregnancy, marital status, sexual orientation, gender reassignment, veteran status, or other protected category