Data Engineer

This is a fully remote position, open to applicants in South Africa, +5 more countries.

📋 Description

• Design, construct, and sustain scalable ETL and ELT data pipelines.

• Develop and enhance data architectures, databases, and data warehouses.

• Integrate data from diverse sources, APIs, and third-party platforms.

• Ensure data quality, accuracy, consistency, reliability, and security.

• Monitor, troubleshoot, and optimize data pipelines and workflows.

• Collaborate with analytics, engineering, and business teams to identify and fulfill data requirements.

• Establish data governance standards and best practices for data management.

• Enhance data storage, processing speeds, and query performance.

• Support business intelligence, reporting, and analytics initiatives.

• Maintain documentation for data models, workflows, and technical processes.

⛳️ Requirements

• A minimum of 2 years of experience in data engineering, data warehousing, or a related field.

• Proficient in SQL with a solid understanding of database management.

• Expertise in Python, Java, Scala, or other pertinent programming languages.

• Hands-on experience with ETL/ELT tools and constructing data pipelines.

• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.

• Practical experience with Snowflake, Redshift, BigQuery, or Databricks.

• Knowledge of Airflow or Prefect.

• Understanding of data modeling, governance, and data quality best practices.

• Experience managing large datasets and working with distributed systems is a plus.

• Strong analytical, problem-solving, and communication skills.

• Ability to work independently while also collaborating with a remote team.

🏝️ Benefits

• Competitive compensation based on experience, technical skills, and location.

• Fully remote work with the flexibility to work from any location.

• Opportunities for career development through innovative, high-impact projects.

• Long-term career growth alongside ambitious, expanding global organizations.

• Continuous learning and exposure to emerging data technologies, cloud platforms, and large-scale data environments.

• Collaborative environment with talented engineers, analysts, and business stakeholders.

• Modern tech stack featuring cutting-edge data tools, technologies, and cloud-based solutions.