About Us:
As a Mid-level Data Analytics 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.
- At least 3–4 years of professional experience working with data analysis, ETL development, and Python-based data processing.
- Solid experience working with AWS services and cloud-native data platforms.
- Experience developing and maintaining data pipelines and working with modern data warehouse solutions such as Snowflake.
- Hands-on experience with data visualization platforms such as Tableau or Power BI.
- Practical knowledge of workflow orchestration tools, particularly Apache Airflow.
- Strong analytical mindset with solid problem-solving capabilities.
- Ability to work both autonomously and collaboratively within a team environment.
- Strong attention to detail with a focus on maintaining data quality and reliability.
- Minimum Upper Intermediate English (B2) or Proficient (C1).
Tasks and Responsibilities:
- Support the development and maintenance of a Snowflake-based data warehouse, building data pipelines that integrate multiple AWS services.
- Assist in implementing and optimizing data pipelines using AWS tools such as DMS, Glue, and Lambda to improve data ingestion and processing.
- Contribute to data migration, integration, and operational processes involving both relational and non-relational databases.
- Monitor the performance and reliability of data systems and propose improvements to maintain efficient operations.
- Develop dashboards and reports using tools like QuickSight or Metabase to present insights to internal teams and external stakeholders.
- Participate in machine learning initiatives by executing scripts and assisting with model optimization tasks.
- Design, schedule, and maintain data workflows using Apache Airflow (preferably Amazon MWAA) to ensure reliable orchestration of data pipelines.
Soft Skills:
- Responsibility
- Proactivity
- Flexibility
- Great communication skills
