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IT Service and Support Engineer for Helpdesk - Office Based Umhlanga
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- Eazi Access RentalJohannesburg, Gauteng
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2nd Line Engineer
Often replies in 1 dayBabble CloudCape Town, Western Cape- Ensure customer calls are promptly attended to, providing efficient and effective support.
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- ElleMargate, KwaZulu-Natal
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- GEW Technologies (Pty) LtdPretoria, Gauteng
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- Standard BankJohannesburg, Gauteng
- Apply agreed standards and tools, to achieve a well-engineers result.
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- InspiredJohannesburg, Gauteng
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- RSAWEBCape Town, Western Cape
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Job Post Details
This job has expired on Indeed
Reasons could include: the employer is not accepting applications, is not actively hiring, or is reviewing applicationsData Engineer - job post
Durbanville, Western Cape
Permanent
Location
Durbanville, Western Cape
Full job description
Are you passionate about building powerful data solutions that drive real business impact? STADIO is looking for a skilled and motivated Mid-Level Data Engineer to join our dynamic Continuous Improvement & Innovation team. In this key role, you’ll help shape the backbone of our data infrastructure—designing and maintaining robust data pipelines and aggregation layers that empower data-driven decision making across the organisation. If you thrive in a collaborative environment, believe in the power of data to drive improvement initiatives and are excited about working with cutting-edge technologies we’d love to hear from you.
About the Role
STADIO is seeking a Mid-Level Data Engineer to join our dynamic Continuous Improvement and Innovation team. In this role, you will play a key part in our continuous improvement lifecycle by developing the data infrastructure that powers data-driven decision making across the organisation. You will work closely with our Analytics Engineer to build and maintain robust data pipelines, a scalable data aggregation layer, and an efficient reporting environment. This is an exciting opportunity for a data engineering professional with a passion for large datasets and modern cloud technologies to make a real impact in a collaborative, forward-thinking environment.
Key Responsibilities
Build and Maintain Data Pipelines: Design, develop, and manage robust data pipelines to ingest, transform, and load data from various sources into our data platform.
Develop Data Aggregation Layer: Create and optimise a scalable data aggregation layer (data warehouse/data lakehouse) that consolidates large datasets and supports efficient querying and reporting.
Collaborate on Data Solutions: Work closely with the Analytics Engineer and other stakeholders to understand data needs and ensure the data architecture supports analytical and reporting requirements.
Ensure Data Quality and Performance: Implement data validation checks, monitoring, and alerting to ensure data accuracy, reliability, and optimal pipeline performance.
Support Data-Driven Decision Making: Partner with analytics and business teams to provide the data foundations for dashboards, reports, and insights that drive strategic decision-making. Drive the implementation of a reporting tool from where staff can do self-service reporting.
Continuous Improvement: Identify opportunities to improve existing data processes and contribute innovative ideas to enhance our data infrastructure as part of the continuous improvement lifecycle.
REQUIREMENTS
Qualifications and Skills Required
Education and Experience
o Bachelor’s degree in Engineering, Information Systems, Computer Science, or a related field.
o 4+ years of hands-on experience in data engineering or a similar role, with a track record of working on large-scale datasets and building data aggregation layers.
Technical Skills:
o Modern Data Stack Proficiency: Practical experience building data pipelines in a modern cloud environment. Familiarity with data lake architectures, SQL databases, and data integration tools on Azure (or similar platforms) is required.
o SQL and Programming Skills: Advanced SQL skills for data querying and transformation. Proficiency in at least one programming or scripting language (e.g., Python, .NET) for data processing.
o Data Modeling Knowledge: Solid understanding of data modeling techniques and designing scalable schema for analytics.
o Performance Tuning: Knowledge of optimising database and data pipeline performance (indexing, partitioning, caching strategies).
o Expertise in Microsoft Data Technologies: Strong experience with Microsoft’s data stack, especially Microsoft Fabric and its underlying components. Proficiency in tools such as Azure Data Factory (for ETL/ELT pipelines) and Azure Synapse Analytics (for data warehousing and big data processing) will be an advantage.
o Additional Cloud and Big Data Tools: Exposure to other cloud data services and tools (such as Azure Databricks, Azure Data Lake Storage, Power BI, or comparable tools on AWS/GCP) will be an advantage.
o Automation and Orchestration: Experience with workflow orchestration tools and CI/CD pipelines for data (e.g., Azure Data Factory pipelines, Git integration, DevOps for data processes).
Preferred Skills and Attributes:
o Analytical Mindset: Strong problem-solving skills and the ability to translate business requirements into efficient data solutions. Attention to detail in ensuring data accuracy and integrity.
o Communication and Teamwork: Excellent communication skills with the ability to work effectively in a collaborative team environment. Able to explain complex data concepts to non-technical stakeholders when needed.
o Agile Methodology: Comfortable working in Agile/Scrum teams and using tools for ticketing and collaboration (Azure DevOps, JIRA, etc.).
o Continuous Learner: Enthusiasm for staying up-to-date with emerging data technologies and best practices. A proactive attitude towards learning and continuous improvement will fit well with our culture.
Why Join Us?
At STADIO, we pride ourselves in fostering a collaborative and innovative culture. You will join a group of professionals who are passionate about leveraging technology and data to drive continuous improvement. We offer a supportive environment where new ideas are encouraged and successes are celebrated.
This role offers the opportunity to be part of a dynamic team focused on driving innovation and efficiency across the organisation. You will contribute to strategic initiatives that shape the future of data-driven decision making across the organisation.
Purposeful Work: Contribute to meaningful transformation initiatives that not only directly supports the organisation’s mission and long-term success, but also has a meaningful impact on South Africa.
What We Offer
Market-Related Salary: A competitive, market-related salary that values your skills and experience.
Generous Leave Policy: We provide a generous leave allowance to ensure you have a healthy work-life balance and time to recharge.
Positive Work Environment: Be part of a team with a strong, inclusive company culture that values collaboration, innovation, and personal growth.
Professional Growth: Opportunities for training, development, and career advancement as we invest in our employees’ growth.
About the Role
STADIO is seeking a Mid-Level Data Engineer to join our dynamic Continuous Improvement and Innovation team. In this role, you will play a key part in our continuous improvement lifecycle by developing the data infrastructure that powers data-driven decision making across the organisation. You will work closely with our Analytics Engineer to build and maintain robust data pipelines, a scalable data aggregation layer, and an efficient reporting environment. This is an exciting opportunity for a data engineering professional with a passion for large datasets and modern cloud technologies to make a real impact in a collaborative, forward-thinking environment.
Key Responsibilities
Build and Maintain Data Pipelines: Design, develop, and manage robust data pipelines to ingest, transform, and load data from various sources into our data platform.
Develop Data Aggregation Layer: Create and optimise a scalable data aggregation layer (data warehouse/data lakehouse) that consolidates large datasets and supports efficient querying and reporting.
Collaborate on Data Solutions: Work closely with the Analytics Engineer and other stakeholders to understand data needs and ensure the data architecture supports analytical and reporting requirements.
Ensure Data Quality and Performance: Implement data validation checks, monitoring, and alerting to ensure data accuracy, reliability, and optimal pipeline performance.
Support Data-Driven Decision Making: Partner with analytics and business teams to provide the data foundations for dashboards, reports, and insights that drive strategic decision-making. Drive the implementation of a reporting tool from where staff can do self-service reporting.
Continuous Improvement: Identify opportunities to improve existing data processes and contribute innovative ideas to enhance our data infrastructure as part of the continuous improvement lifecycle.
REQUIREMENTS
Qualifications and Skills Required
Education and Experience
o Bachelor’s degree in Engineering, Information Systems, Computer Science, or a related field.
o 4+ years of hands-on experience in data engineering or a similar role, with a track record of working on large-scale datasets and building data aggregation layers.
Technical Skills:
o Modern Data Stack Proficiency: Practical experience building data pipelines in a modern cloud environment. Familiarity with data lake architectures, SQL databases, and data integration tools on Azure (or similar platforms) is required.
o SQL and Programming Skills: Advanced SQL skills for data querying and transformation. Proficiency in at least one programming or scripting language (e.g., Python, .NET) for data processing.
o Data Modeling Knowledge: Solid understanding of data modeling techniques and designing scalable schema for analytics.
o Performance Tuning: Knowledge of optimising database and data pipeline performance (indexing, partitioning, caching strategies).
o Expertise in Microsoft Data Technologies: Strong experience with Microsoft’s data stack, especially Microsoft Fabric and its underlying components. Proficiency in tools such as Azure Data Factory (for ETL/ELT pipelines) and Azure Synapse Analytics (for data warehousing and big data processing) will be an advantage.
o Additional Cloud and Big Data Tools: Exposure to other cloud data services and tools (such as Azure Databricks, Azure Data Lake Storage, Power BI, or comparable tools on AWS/GCP) will be an advantage.
o Automation and Orchestration: Experience with workflow orchestration tools and CI/CD pipelines for data (e.g., Azure Data Factory pipelines, Git integration, DevOps for data processes).
Preferred Skills and Attributes:
o Analytical Mindset: Strong problem-solving skills and the ability to translate business requirements into efficient data solutions. Attention to detail in ensuring data accuracy and integrity.
o Communication and Teamwork: Excellent communication skills with the ability to work effectively in a collaborative team environment. Able to explain complex data concepts to non-technical stakeholders when needed.
o Agile Methodology: Comfortable working in Agile/Scrum teams and using tools for ticketing and collaboration (Azure DevOps, JIRA, etc.).
o Continuous Learner: Enthusiasm for staying up-to-date with emerging data technologies and best practices. A proactive attitude towards learning and continuous improvement will fit well with our culture.
Why Join Us?
At STADIO, we pride ourselves in fostering a collaborative and innovative culture. You will join a group of professionals who are passionate about leveraging technology and data to drive continuous improvement. We offer a supportive environment where new ideas are encouraged and successes are celebrated.
This role offers the opportunity to be part of a dynamic team focused on driving innovation and efficiency across the organisation. You will contribute to strategic initiatives that shape the future of data-driven decision making across the organisation.
Purposeful Work: Contribute to meaningful transformation initiatives that not only directly supports the organisation’s mission and long-term success, but also has a meaningful impact on South Africa.
What We Offer
Market-Related Salary: A competitive, market-related salary that values your skills and experience.
Generous Leave Policy: We provide a generous leave allowance to ensure you have a healthy work-life balance and time to recharge.
Positive Work Environment: Be part of a team with a strong, inclusive company culture that values collaboration, innovation, and personal growth.
Professional Growth: Opportunities for training, development, and career advancement as we invest in our employees’ growth.
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