What Data Engineering Jobs are in Cape Town?

• Lead the design and architecture of end-to-end AI/ML solutions, encompassing data ingestion, preprocessing, model training, deployment, and monitoring.
• Collaborate with data scientists, engineers, and business stakeholders to define AI strategy and roadmap.
• Evaluate and recommend appropriate cloud services (AWS, Azure, GCP) and data platform technologies for AI workloads.
• Develop proofs-of-concept and pilot projects to validate AI solutions and demonstrate business value.
• Ensure AI solutions are scalable, secure, reliable, and compliant with relevant regulations.
• Provide technical guidance and mentorship to development teams on AI best practices.
• Stay updated on emerging trends and technologies in AI, cloud computing, and big data.
• Document architectural designs, technical specifications, and deployment procedures.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• Extensive experience (5+ years) in software architecture, with a significant focus on AI/ML systems and cloud platforms.
• Deep understanding of machine learning algorithms, MLOps principles, and data engineering concepts.
• Proven experience designing and deploying AI solutions on major cloud providers (AWS SageMaker, Azure ML, GCP AI Platform).
• Proficiency in programming languages such as Python and experience with relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of data warehousing, data lakes, and big data technologies (e.g., Spark, Hadoop).
• Excellent analytical, problem-solving, and communication skills.
• Experience in an architect role, demonstrating the ability to define and communicate complex technical strategies.

• Design, develop, and maintain scalable ETL/ELT pipelines for processing large volumes of data.
• Build and manage data warehouses and data lakes on cloud platforms (e.g., AWS, Azure, GCP).
• Implement data quality checks and monitoring to ensure data accuracy and reliability.
• Optimize data retrieval and processing performance.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
• Develop and maintain data models that support business intelligence and analytics.
• Automate data processes using scripting and relevant tools.
• Ensure data security and compliance with relevant regulations.
• Evaluate and recommend new technologies and tools to enhance the data infrastructure.
• Mentor junior data engineers and contribute to best practices in data engineering.

• Extensive experience as a Data Engineer or in a similar role focused on data infrastructure and pipelines.
• Strong proficiency in SQL and experience with various database technologies (relational and NoSQL).
• Expertise in programming languages commonly used for data engineering, such as Python, Scala, or Java.
• Hands-on experience with cloud data services (e.g., AWS RDS, Redshift, S3; Azure SQL Data Warehouse, Data Lake Storage; Google BigQuery, Cloud Storage).
• Familiarity with big data technologies and distributed processing frameworks (e.g., Spark, Hadoop).
• Experience with ETL tools and data pipeline orchestration tools (e.g., Airflow, dbt).
• Understanding of data warehousing principles and data modeling techniques.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills for a remote team environment.
• A Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field, or equivalent professional experience.

Our client is seeking a highly skilled and motivated Senior Financial Data Engineer to join their globally distributed, remote-first team. This role is crucial for designing, building, and maintaining scalable data pipelines and infrastructure that power our client's advanced financial analytics and trading platforms. As a remote-first organization, we embrace asynchronous communication and prioritize output and collaboration over physical presence. You will work with vast datasets, implementing robust data solutions that ensure data quality, accessibility, and performance. This is an exceptional opportunity for an experienced engineer passionate about financial markets and data technologies to make a significant impact from anywhere. You will be an integral part of our innovative Banking & Finance team, contributing to the development of next-generation financial tools and insights. This position is designated as fully remote, requiring a self-disciplined and proactive individual.

• Design, develop, and optimize robust, scalable ETL/ELT pipelines for processing large volumes of financial data.
• Build and maintain data warehousing solutions and data lakes, ensuring data integrity and efficiency.
• Implement data quality checks, monitoring, and alerting systems to ensure data accuracy and reliability.
• Collaborate with data scientists, quantitative analysts, and traders to understand their data requirements and deliver tailored solutions.
• Develop and manage data infrastructure using cloud platforms (e.g., AWS, Azure, GCP) and related technologies.
• Automate data processes and workflows to improve efficiency and reduce manual intervention.
• Ensure data security and compliance with relevant financial regulations and privacy standards.
• Contribute to the architectural design and technology selection for data platforms.
• Troubleshoot and resolve complex data-related issues in a timely manner.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
• Minimum of 6 years of professional experience in data engineering, with a focus on financial data.
• Strong proficiency in SQL and programming languages such as Python or Scala.
• Hands-on experience with big data technologies (e.g., Spark, Hadoop, Kafka) and data warehousing concepts.
• Experience with cloud data platforms (AWS Redshift, S3, Glue; Azure Data Factory, Synapse; GCP BigQuery, Dataflow).
• Familiarity with data modeling techniques and database design principles.
• Understanding of financial markets, trading systems, and financial data types.
• Excellent problem-solving skills and the ability to work independently in a remote setting.
• Strong communication skills, particularly in written and asynchronous communication formats.
• Experience with containerization technologies like Docker and Kubernetes is a plus.

• Competitive salary range of R per annum.
• Fully remote work environment, offering unparalleled flexibility.
• Comprehensive health insurance coverage, including international options if applicable.
• Generous performance-based bonus structure.
• Annual budget for professional development, conferences, and online courses.
• Home office setup allowance.
• Flexible working hours to accommodate different time zones.
• Company-provided laptop and necessary software licenses.
• Opportunities to work on challenging and impactful projects within the global financial markets.

Our client, a forward-thinking energy company, is seeking a highly skilled and motivated Reservoir Engineer with a strong focus on data analysis to join their remote team. This position, designed for a professional who thrives in a fully remote work environment, will be instrumental in analyzing complex reservoir data, developing predictive models, and providing critical insights to optimize hydrocarbon recovery. You will work with diverse datasets from various fields within the Oil & Gas sector, leveraging advanced analytical tools and techniques. The role demands exceptional technical acumen, a proactive approach to problem-solving, and the ability to communicate findings clearly to stakeholders, regardless of physical location. This is an exceptional opportunity to contribute significantly to our client's strategic decisions without the need for relocation or office presence, truly embodying a remote-first ethos.

• Analyze vast amounts of reservoir data, including well logs, core data, production history, and seismic attributes.
• Develop and implement advanced statistical and machine learning models for reservoir characterization and performance prediction.
• Perform decline curve analysis, material balance calculations, and volumetric assessments.
• Utilize reservoir simulation software to test various development scenarios and optimization strategies.
• Generate detailed reports and visualizations that clearly communicate complex analytical findings and recommendations.
• Collaborate effectively with geoscientists, production engineers, and management through virtual communication channels.
• Identify opportunities for data-driven improvements in reservoir management and production strategies.
• Stay current with the latest advancements in data science, machine learning, and their application in reservoir engineering.
• Ensure data integrity and accuracy throughout the analysis process.
• Provide technical support and guidance on data interpretation to other team members.

• Bachelor's or Master's degree in Petroleum Engineering, Data Science, or a related quantitative field.
• Minimum of 5 years of experience in reservoir engineering, with a significant emphasis on data analysis and modeling.
• Proven expertise in statistical analysis, data mining, and machine learning techniques relevant to the oil and gas industry.
• Proficiency with data analysis tools and programming languages such as Python (Pandas, NumPy, Scikit-learn) or R.
• Experience with reservoir simulation software (e.g., ECLIPSE, INTERSECT) is a strong asset.
• Excellent analytical and problem-solving skills with a keen eye for detail.
• Strong ability to communicate technical information effectively in writing and verbally in a remote setting.
• Self-motivated and able to work independently with minimal supervision.
• Experience in managing and analyzing large, complex datasets.
• A collaborative spirit, essential for remote team interactions.

Our client offers a highly competitive salary, flexible working hours, and a comprehensive remote work support package. Benefits include private health insurance, a contribution-based retirement plan, and generous provisions for professional development and online training. This fully remote position offers unparalleled flexibility and the opportunity to work on diverse and challenging projects within the Oil & Gas industry from anywhere. Our client is dedicated to fostering a culture of innovation and empowering its remote workforce.

Our client, a pioneering technology company dedicated to digital transformation in the Oil & Gas industry, is seeking a highly motivated Remote Upstream Data Engineer. This is a fully remote position, providing an excellent opportunity to work from anywhere. You will be responsible for designing, building, and maintaining robust data pipelines and infrastructure to support our client's advanced upstream analytics and digital oilfield solutions. The ideal candidate has a strong background in data engineering, cloud technologies, and experience with oil and gas data types. You will work closely with data scientists, geologists, and reservoir engineers to ensure the availability, quality, and accessibility of critical upstream data. We are looking for a proactive, detail-oriented engineer who thrives in a remote environment and is passionate about enabling data-driven decision-making in the energy sector.

• Design, develop, and maintain scalable data pipelines for ingesting, transforming, and storing upstream oil and gas data (e.g., well logs, seismic, production, drilling data).
• Implement data warehousing solutions and data lake architectures on cloud platforms (e.g., AWS, Azure, GCP).
• Ensure data quality, integrity, and security across all data assets.
• Optimize data infrastructure for performance, reliability, and cost-efficiency.
• Collaborate with data scientists and analysts to understand their data needs and provide tailored data solutions.
• Develop and manage ETL/ELT processes using modern data engineering tools and frameworks.
• Automate data processes and monitor system performance, troubleshooting issues as they arise.
• Stay up-to-date with emerging data engineering technologies and best practices.
• Document data architecture, pipelines, and processes comprehensively.

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
• Minimum of 5 years of experience in data engineering, with a focus on building and managing data pipelines.
• Proven experience with cloud platforms (AWS, Azure, or GCP) and their data services (e.g., S3, ADLS, Redshift, Snowflake, BigQuery).
• Proficiency in SQL and at least one programming language commonly used in data engineering (e.g., Python, Scala, Java).
• Experience with big data technologies such as Spark, Hadoop, or Kafka.
• Familiarity with data modeling techniques and database design.
• Strong understanding of data quality principles and data governance best practices.
• Excellent problem-solving skills and the ability to work independently in a remote setting.
• Effective communication and collaboration skills.
• Experience working with upstream oil and gas data is highly preferred.

This fully remote position offers unparalleled flexibility and the opportunity to work on transformative projects in the Oil & Gas digital space. Our client provides a competitive salary, performance bonuses, and a comprehensive benefits package, including excellent health coverage and retirement contributions. Continuous learning and professional development are strongly supported through training programs and resources. The company fosters a vibrant, collaborative remote work culture that values innovation and teamwork. This role offers significant impact and career growth potential, allowing you to shape the future of upstream data management from the convenience of your home office.

Our client, a rapidly growing data analytics company, is seeking a highly skilled and experienced Lead Data Engineer to join their fully remote team. This role is instrumental in designing, building, and maintaining scalable big data infrastructure and pipelines that power our client's advanced analytics and machine learning initiatives. You will work with cutting-edge technologies to process, store, and analyze massive datasets, ensuring data quality, reliability, and accessibility. The ideal candidate has a deep understanding of distributed systems, data warehousing, and ETL processes, coupled with strong leadership skills to guide junior engineers. This is an unparalleled opportunity to shape the data architecture of a forward-thinking company in a remote-first setting, contributing to data-driven innovation on a global scale.

• Design, develop, and implement robust and scalable big data solutions and data pipelines.
• Build and optimize ETL/ELT processes for ingesting, transforming, and preparing large datasets from various sources.
• Manage and maintain cloud-based data platforms (e.g., AWS, Azure, GCP) and associated services.
• Implement data warehousing strategies and data lake architectures.
• Ensure data quality, integrity, and governance across all data platforms.
• Collaborate with data scientists, analysts, and software engineers to understand data needs and deliver solutions.
• Monitor system performance, troubleshoot issues, and implement performance optimizations.
• Develop and maintain documentation for data architectures, pipelines, and processes.
• Lead and mentor junior data engineers, fostering a collaborative and high-performing team environment.
• Stay current with emerging big data technologies and best practices.

• Master's degree or Ph.D. in Computer Science, Engineering, or a related quantitative field.
• Minimum of 7 years of experience in data engineering, with a strong focus on big data technologies.
• Proficiency in programming languages such as Python, Scala, or Java.
• Extensive experience with big data processing frameworks like Apache Spark, Hadoop, Flink.
• Hands-on experience with cloud data platforms (AWS: S3, EMR, Redshift; Azure: ADLS, Databricks, Synapse; GCP: GCS, Dataproc, BigQuery).
• Strong understanding of SQL, NoSQL databases, data warehousing concepts, and data modeling.
• Experience with workflow orchestration tools (e.g., Airflow, Oozie).
• Excellent problem-solving, analytical, and troubleshooting skills.
• Strong communication and collaboration skills, with the ability to work effectively in a remote team.
• Experience with CI/CD practices for data pipelines is a plus.

Our client offers an industry-leading salary and a comprehensive benefits package, including superior health coverage, retirement planning assistance, and generous paid time off. As a fully remote employee, you will benefit from a flexible work schedule and a dedicated home office stipend to ensure a productive work environment. Continuous learning and professional development are highly valued, with access to extensive online training resources, conference attendance, and opportunities for certification. Our client is committed to building a strong remote culture that promotes work-life balance, collaboration, and individual growth. Join our innovative team and play a key role in advancing our big data capabilities.