Data Engineer

Data Engineer (P848)

About Us:

As a Senior Data Engineer at Kenility, you’ll join a tight-knit family of creative developers, engineers, and designers who strive to develop and deliver the highest quality products into the market.

 

Technical Requirements:

  • Bachelor’s degree in Computer Science, Software Engineering, or a related field.
  • Advanced SQL skills for querying, managing, and optimizing relational databases, with the ability to handle complex queries and large volumes of data efficiently.
  • Strong command of Python, particularly in the use of data processing libraries like Pandas, for building scalable and maintainable scripts and automation tools.
  • Solid experience with PySpark for distributed processing of large-scale datasets, including familiarity with Spark’s DataFrame API, RDDs, and performance tuning techniques.
  • In-depth knowledge of ETL methodologies and proven ability to design and implement efficient data pipelines ensuring high data quality.
  • Skilled in data modeling practices, including the creation of logical and physical schemas aligned with reporting and querying efficiency.
  • Experience working with RDBMS platforms such as Oracle or MySQL, with an understanding of database design, indexing, and query performance optimization.
  • Understanding of data warehousing principles and experience in building data warehouse solutions tailored for analytics and business intelligence.
  • Proficiency in Unix/Linux systems for workflow management, automation scripting, and system operations.
  • Capable of writing shell scripts to streamline data processing tasks and support integration within the system infrastructure.
  • Familiarity with implementing automated testing strategies for ETL processes to safeguard data integrity and system reliability.
  • Minimum Upper Intermediate English (B2) or Proficient (C1).

 

Tasks and Responsibilities:

  • Design, implement, and maintain scalable ETL workflows and data pipelines that support seamless data ingestion, transformation, and storage.
  • Develop automated systems for validating and monitoring data quality across platforms, ensuring accuracy and consistency.
  • Collaborate with cross-functional teams to translate business and analytical requirements into robust technical solutions.
  • Monitor data infrastructure performance and proactively optimize for scalability, reliability, and cost-effectiveness.
  • Troubleshoot and resolve issues related to data systems, providing thorough analysis and implementing long-term fixes.
  • Maintain detailed documentation of pipeline architectures, processes, and system components, while actively contributing to code and design reviews.
  • Keep pace with emerging trends and tools in data engineering to introduce improvements and innovation into existing workflows.
  • Support the professional growth of junior team members through mentoring and technical guidance.

 

Soft Skills:

  • Responsibility
  • Proactivity
  • Flexibility
  • Great communication skills