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 expertise in SQL, with the ability to design, query, and optimize complex data pipelines and semantic layers for large-scale data operations.
- Proven experience using Databricks for building and managing data pipelines, handling ETL/ELT processes, and leveraging its collaborative tools and cloud integrations.
- Solid backend development skills in Python, including scripting, automation, and the use of relevant libraries for data engineering tasks.
- Strong knowledge of data governance, covering aspects such as data quality, lineage, cataloging, and compliance with regulatory standards.
- Demonstrated ability to implement data security practices, including access control, encryption, and secure data handling to protect sensitive information.
- Hands-on experience working within agile frameworks such as Scrum or Kanban, with a focus on iterative development and cross-functional collaboration.
- Familiarity with supporting AI/ML model integration and deployment within data pipelines to ensure robust backend data infrastructure.
- Understanding of Databricks’ AI and Business Intelligence features to enhance analytical capabilities and model deployment.
- Minimum Upper Intermediate English (B2) or Proficient (C1).
Tasks and Responsibilities:
- Lead the creation, development, and optimization of scalable data pipelines using Databricks and SQL to support analytics and business intelligence efforts.
- Collaborate with diverse engineering teams to transition legacy data systems to modern cloud-based solutions, ensuring smooth migration and efficiency.
- Develop and manage semantic layers and metrics views to enable scalable and consistent self-service reporting across various business functions.
- Address data infrastructure backlog tasks, including enhancements, bug resolutions, and feature developments within an agile workflow.
- Enforce data governance and security standards throughout all data-related initiatives, ensuring the protection of sensitive data and regulatory compliance.
- Facilitate the integration of AI/ML models by ensuring seamless backend data access and supporting necessary infrastructure.
- Engage in agile activities such as sprint planning, daily stand-ups, and retrospectives to maintain transparency and collaboration within the team.
- Continuously assess and suggest new technologies and methodologies to enhance data engineering workflows and infrastructure.
Soft Skills:
- Responsibility
- Proactivity
- Flexibility
- Great communication skills
