About Us:
As a 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.
- 3+ years of hands-on experience in Data Engineering or in a similar position, with a solid background in ETL development and data pipeline implementation.
- Strong command of SQL and Python for building and maintaining data processing solutions.
- Practical experience using PySpark and/or Pandas to manage and process large volumes of data.
- Good understanding of data warehousing principles and exposure to platforms such as AWS Redshift, Google BigQuery, or Snowflake, including performance tuning for high-volume environments.
- Proven expertise in database development, data modeling, schema design, and optimization strategies that support scalability.
- Experience creating and maintaining automated tests for data pipelines and related processes.
- Familiarity with Unix/Linux environments and shell scripting for development and operational tasks.
- Working knowledge of CI/CD practices applied to deploying and maintaining data processing jobs.
- Solid understanding of the Software Development Life Cycle and experience collaborating within cross-functional development teams.
- Strong knowledge of Credit and Fintech domains, with a clear understanding of how data supports products, workflows, and business operations in these areas.
- Minimum Upper Intermediate English (B2) or Proficient (C1).
Tasks and Responsibilities:
- Build, enhance, and support reliable data pipelines and ETL workflows to move and transform data into the data warehouse.
- Develop and improve SQL queries and Python-based processing jobs to handle large-scale data operations efficiently.
- Establish automated validation and quality control mechanisms to preserve data consistency and accuracy.
- Track pipeline behavior, identify technical issues, and implement improvements to increase performance, stability, and scalability.
- Work closely with product managers, analysts, and other stakeholders to understand business needs and deliver effective data-driven solutions.
- Produce and maintain technical and design documentation related to pipelines, architectures, and supporting systems.
- Take part in design discussions and code reviews to help uphold engineering best practices and code quality.
- Apply data modeling principles and schema design approaches that enable scalable storage and efficient querying.
- Support the adoption and integration of CI/CD workflows for the deployment and management of data jobs.
- Follow SDLC standards and contribute actively as part of the development team, including updates and improvements to ETL tools and processes.
Soft Skills:
- Responsibility
- Proactivity
- Flexibility
- Great communication skills
