Data Engineer

Role:

Years of Experience:

Key Skills:

Key responsibilities

• Design and build data infrastructure:

  Create and maintain scalable systems, databases, and data pipeline architectures to support data collection, storage, and processing.

• Transform and prepare data:

  Develop algorithms and methods to clean, combine, and transform raw data into a structured format suitable for analytics and machine learning.

• Ensure data quality and security:

  Implement data validation methods, monitor workflows, and ensure compliance with data governance and security policies.

• Collaborate with teams:

  Work with data scientists, analysts, and business stakeholders to understand data requirements and deliver valuable insights for decision-making.

• Troubleshoot and optimize:

  Monitor systems, identify and correct errors, and optimize existing frameworks to improve performance.

Essential skills and qualifications

• Programming:

  Strong proficiency in languages like Pyspark, Python and SQL.

• Databases and big data technologies:

  Expertise in database systems and big data tools like Hadoop and Spark.

• Data architecture:

  A solid understanding of how to structure and manage data systems.

• Problem-solving:

  The ability to creatively solve problems and apply data science to business needs.

• Communication:

  Excellent communication skills to collaborate with different teams and stakeholders.

• Education:

  A bachelor's degree in a field like computer science, information technology, or applied mathematics is often required.

• Technical Skills:

• Programming Languages:

  Strong proficiency in

  Python

  and

  SQL

  is essential. Java or Scala is a plus.

• Databases:

  Experience with relational and NoSQL databases.

• Big Data Technologies:

  Experience with Apache Hadoop,

  Spark

  , or

  Kafka

  .

• Cloud Platforms:

  Proficiency in AWS, Azure, or GCP and their data services.

• ETL & Workflow Management:

  Experience designing ETL pipelines using tools like Apache Airflow.

• Data Modeling:

  Understanding of data modeling, schema design, and data warehousing concepts.

Soft Skills:

• Problem-solving and analytical abilities.
• Strong communication skills.
• Ability to work independently and collaboratively.
• Detail-oriented with a commitment to data accuracy.

Education and Experience:

• Bachelor's degree in a relevant technical field.
• Experience with data visualization tools (Tableau, Power BI) is a plus.