Data Ops ML Engineer

Responsibilities

As a Data Ops ML Engineer, you will play a crucial role in processing structured and unstructured data for data science activities. Your responsibilities will include:

Undertaking the processing of structured and unstructured data for data science activities.

Supporting the analysis of large information to identify trends and patterns, providing feedback to the business.

Assisting in designing and implementing scalable processes for ingesting and transforming datasets.

Designing, implementing, and maintaining data pipelines from various sources.

Ingesting large, complex datasets meeting functional and non-functional requirements.

Implementing and training machine learning, predictive analytics, data mining, and AI models for proactive decision-making.

Working with large volumes of structured and unstructured data, building AI/ML and predictive modeling solutions through automated data pipelines.

Solving challenges related to working with diverse data formats, enabling innovative solutions.

Designing and building bulk and delta data lift patterns for optimal extraction, transformation, and loading.

Supporting the organization's cloud strategy, aligning with data architecture and governance.

Engineering data in appropriate formats for downstream customers, risk, and product analytics.

Developing APIs for returning data to Enterprise Applications.

Identifying, designing, and implementing process improvement activities for efficiency and automation.

Collaborating with stakeholders to understand data requirements and applying technical knowledge to solve business problems.

Providing support in the operational environment with relevant support teams for data services.

Creating and maintaining functional requirements and system specifications for data architecture.

Supporting the testing and deployment of new services and features.

Qualifications Requirements

Matric, with a degree in Computer Science, Business Informatics, Mathematics, Applied Statistics/Applied Mathematics Physics, or Data Engineering.

Certification in data, data science, or artificial intelligence.

Experience/Requirements

3 to 5+ years of data engineering experience.

3 to 5+ years of Machine learning/Artificial Intelligence and Statistical algorithm development.

3+ years of experience with any data warehouse technical architectures, ETL/ELT, and reporting/analytics tools.

Working with large volumes of structured and unstructured data, leveraging them to build AI/ML and predictive modeling solutions through end-to-end automated data pipelines.

Deep and extensive AWS knowledge and skills: Glue, S3, Lambda, IAM, CloudFormation.

DBA ability and knowledge across at least 2 platforms (e.g., TSQL, SAS, PSQL, IBM VSAM, and DB2) is beneficial.

Some experience with the Python programming language.

Experience with designing and implementing Cloud (AWS) solutions, including the use of available APIs.

Some experience with Dev/OPS architecture, implementation, and operation would be advantageous.

Minimum bachelors degree in quantitative management (decision sciences) or Computer Science/Statistics/Applied Statistics/Applied Mathematics.

Knowledge of Engineering and Operational Excellence using standard methodologies.

Best practices in software engineering, data management, data storage, data computing, and distributed systems to solve business problems with data.

Some experience in applying SAFe/Scrum/Kanban methodologies would be advantageous.

Knowledge and understanding of the business process management lifecycle, covering design, modeling, execution, monitoring, and optimization, as well as business process re-engineering.

Good problem-solving skills: The ability to exercise judgment in solving technical, operational, and organizational challenges, to identify issues proactively, to present solutions and options leading to resolution.

Good programming, performance tuning, and troubleshooting skills, using the latest popular programming languages such as Python, Scala, Java, and suite of Microsoft languages (C# and F# preferable).

Location: Remote

Salary: R80 000 R96 000

Duration: 12 Months