• As a Senior Data Engineer at ICEA LION, you will develop, optimise, and manage our data lake, data pipelines, and data infrastructure to power analytics, reporting, advanced analytics, machine learning & AI. Your role will focus on building scalable data products that unify data across all interactions and touchpoints. Working with cross-functional teams, you will enforce data governance standards and drive a collaborative, data-driven culture.

Roles and Responsibilities

• Set up, manage, and maintain the company’s data analytics systems, including the operational data store, feature store, and data warehouse, to support informed decision-making.
• Create and manage processes (ETL/ELT) for collecting, cleaning, and transforming data from different sources.
• Build and improve data structures to support reporting, advanced analytics, and machine learning projects.
• Ensure data queries run efficiently while keeping costs low and making the best use of resources.
• Work closely with technology and data analytics teams to develop customized data solutions and include machine learning insights.
• Set up and manage machine learning workflows to make sure models run smoothly and reliably.
• Implement data quality checks, follow governance rules, and enforce security to protect and control access to data.
• Automate tasks and improve processes using tools to ensure stable and scalable data pipelines.
• Clearly document all processes and share knowledge to help the team adopt best practices.​

Requirements

Academic and Professional Qualifications

• Bachelor’s Degree in Computer Science, Data Science, Information Technology, Engineering, or a related field.
• Professional Data Engineer Certification is a plus.
• Master’s Degree in Data Science, Computer Science, Information Systems, or a related discipline.
• Extensive knowledge of data warehousing concepts, including dimensional modelling and data marts.
• Minimum of 5-7 years in data engineering, data architecture, or a related field.
• Experience in leading data projects or teams is highly desirable.
• Advanced proficiency in SQL and NoSQL with hands-on experience creating complex queries and data transformations.
• Proven experience with cloud-based data engineering tools such as Cloud Storage, Data flow, Cloud Composer, Cloud Functions, and AWS Glue.
• Strong familiarity with ETL/ELT tools (e.g., Apache Beam, Apache Airflow, SSIS, Data flow, dbt) for building and maintaining data pipelines.
• Proficient in scripting languages like Bash, Python, and JavaScript to support automation and integration tasks.
• Skilled in managing and optimizing large datasets for performance and cost-efficiency.
• Excellent communication skills with a demonstrated ability to work collaboratively in cross-functional teams.
• Familiarity with Machine Learning (ML) techniques and Language Learning Models (LLMs) to support data-driven applications.