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.
Apply via :
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