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Senior Data Engineer

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Summary

Senior Data Engineer building and maintaining data pipelines, warehouses, and data lakes for a client's analytics team in Richards Bay, South Africa, on a hybrid work model. Core stack includes SQL, Python/Scala, Spark/Hadoop, cloud data warehouses (Redshift/Synapse/BigQuery), and Airflow.

About the Role

Our client is seeking a talented Senior Data Engineer to join their analytics team in Richards Bay . You will be instrumental in building and maintaining robust data pipelines, ensuring the availability and integrity of data for analytics and business intelligence purposes. This role involves working with large datasets, designing data models, and optimizing data storage and retrieval processes to support data-driven decision-making. Join a collaborative team that values innovation and leverages data to drive strategic initiatives, benefiting from a hybrid work arrangement that fosters both team cohesion and personal flexibility.

Key Responsibilities

  • Design, build, and maintain scalable and reliable data pipelines using ETL/ELT processes.
  • Develop and manage data warehouses and data lakes, optimizing for performance and cost-efficiency.
  • Implement data modeling techniques to support business intelligence and analytical requirements.
  • Ensure data quality, integrity, and security throughout the data lifecycle.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver actionable insights.
  • Monitor data systems, troubleshoot issues, and implement solutions to ensure optimal performance and availability.

Requirements

  • Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
  • 5+ years of experience in data engineering , with a strong understanding of data warehousing concepts and technologies.
  • Proficiency in SQL and experience with programming languages such as Python or Scala.
  • Hands-on experience with big data technologies (e.g., Spark, Hadoop) and cloud data services (AWS Redshift, Azure Synapse, GCP BigQuery).
  • Familiarity with ETL tools and data orchestration frameworks (e.g., Apache Airflow).
  • Strong analytical and problem-solving skills, with a keen eye for detail and data accuracy.

Benefits

  • Competitive salary and performance-related bonuses.
  • Comprehensive medical coverage and retirement planning options.
  • Opportunities for continuous learning and professional development in data technologies.
  • A hybrid work model providing flexibility and a balance between office collaboration and remote work.
  • A dynamic work environment focused on leveraging data to achieve business objectives.

Skills

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See also

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