2 min read
| 27 Feb, 2024 |
Written by Rochelle Wickramasinghe

Job Description Template – Data Engineer

Use this Data Engineer job description to attract talent, and customize it to reflect the specific duties and responsibilities relevant to your company.

Job Summary

We are seeking a skilled and motivated Data Engineer to join our team. The Data Engineer will play a crucial role in designing, building, and maintaining data pipelines, data warehouses, and other data infrastructure solutions. The ideal candidate should have a strong background in data engineering, proficiency in relevant technologies, and a passion for turning raw data into actionable insights.


  1. Design, develop, and maintain scalable and efficient data pipelines and ETL processes to support data ingestion, transformation, and storage.
  2. Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
  3. Implement data models, schemas, and structures to support data analysis, reporting, and visualization.
  4. Optimize and tune database systems and queries for performance, scalability, and reliability.
  5. Monitor data pipelines and systems to ensure data quality, integrity, and security.
  6. Implement data governance policies, standards, and best practices to ensure compliance and data security.
  7. Work closely with data analysts, data scientists, and business stakeholders to understand data needs and deliver actionable insights.
  8. Stay up-to-date with emerging technologies, tools, and trends in data engineering and incorporate them into projects when appropriate.
  9. Document data engineering processes, workflows, and technical specifications.
  10. Provide technical support and assistance to end-users as needed.


  • Proven experience in data engineering, with experience in designing, building, and maintaining data infrastructure solutions.
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. Master’s degree preferred.
  • Proficiency in programming languages commonly used in data engineering, such as Python, SQL, Scala, or Java.
  • Strong understanding of database systems, data modeling, and SQL query optimization.
  • Experience with data warehousing solutions and cloud-based data platforms (e.g., AWS, Azure, Google Cloud).
  • Familiarity with big data technologies and frameworks, such as Hadoop, Spark, Kafka, or Flink.
  • Experience with data pipeline orchestration tools, such as Apache Airflow, Luigi, or Prefect.
  • Knowledge of data integration techniques and tools (e.g., Talend, Informatica, Matillion).
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and collaboration skills.
  • Ability to work independently and in a team environment.

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