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.
- Hands-on experience with ETL/ELT processes, including developing and maintaining scalable data ingestion and transformation pipelines.
- Experience working with Google BigQuery as a cloud data warehouse, including data loading, transformation, and optimization practices.
- Understanding of data lake and data warehouse architectures, with the ability to support data flows between data lakes, BigQuery, and business-oriented data marts.
- Knowledge of source data analysis and source-to-target mapping to translate business requirements into technical data specifications.
- Experience implementing complex data transformation logic while maintaining data quality, accuracy, and timely availability.
- Familiarity with BigQuery performance and cost optimization practices, including schema design, partitioning, clustering, query optimization, efficient resource consumption, and storage lifecycle management.
- Ability to develop and execute unit tests for data pipelines and transformation processes, validating functionality, data integrity, and performance.
- Understanding of scalable, resilient, and fault-tolerant data pipeline design to accommodate increasing data volumes and evolving business needs.
- Experience contributing to technical estimation and development planning within an Agile delivery environment.
- Minimum Upper Intermediate English (B2) or Proficient (C1).
Tasks and Responsibilities:
- Analyze source data systems and collaborate with key stakeholders to define comprehensive source-to-target mappings, translating business needs into clear technical specifications for data ingestion and transformation.
- Estimate development efforts and required resources to support sprint planning and ensure alignment with the project roadmap within an Agile environment.
- Design, develop, and maintain scalable ETL/ELT pipelines to efficiently move data from the data lake into BigQuery and business-specific data marts.
- Implement complex data transformation processes while ensuring data accuracy, quality, and timely availability for analytical and operational needs.
- Develop and execute comprehensive unit tests for data pipelines and transformation logic, validating functionality, data integrity, and performance before deployment.
- Partner with the Data Architect, Scrum Master, Program Manager, and Business Analyst to maintain architectural alignment, support Agile delivery, meet project timelines, and accurately address business requirements.
- Apply best practices for BigQuery schema design, partitioning, clustering, and query optimization while promoting efficient resource utilization and storage lifecycle management to control costs.
- Develop resilient, fault-tolerant, and scalable data workflows capable of supporting increasing data volumes and evolving business requirements.
Soft Skills:
- Responsibility
- Proactivity
- Flexibility
- Great communication skills
