Job Vacancies at ICEA Lion Group

• As a Senior Data Engineer at ICEA LION, you will develop, optimize, 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.
• Optional: Master’s Degree in Data Science, Computer Science, Information Systems, or a related discipline.

Experience

• Extensive knowledge of data warehousing concepts, including dimensional modelling and data marts.
• Minimum of 5 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.
• Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure, particularly their data services (e.g., AWS S3, GCP BigQuery).

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• As a Data Governance Specialist, you will lead, implement, and enforce the data governance framework that aligns with organizational strategy. Your role will focus on ensuring high data quality across the data life cycle ensuring ethical use of data while supporting data-driven decision-making. Working with cross-functional teams, you will champion data stewardship, establish best practices, and drive a collaborative culture that values data as a strategic asset. By fostering a culture of accountability and stewardship, you will ensure data serves as a valuable and trusted asset for achieving business objectives

Roles and Responsibilities

• Lead the implementation of the data governance framework.
• Collaborate with key stakeholders to establish policies, standards, and procedures that support business objectives.
• Align data assets with the company’s strategic goals to drive value and efficiency eradicating data gaps to support data driven decision making.
• Conduct regular evaluations of data assets to identify and address gaps impacting strategic outcomes.
• Enhance data quality through consistent standards, training, and improvement initiatives. Profile, cleanse, validate, and monitor data quality to ensure accuracy and reliability.
• Oversee processes for organizing, tracking, and documenting data to improve accessibility and usability.
• Promote a culture of data excellence through stakeholder engagement and capacity building.
• Identify and deploy appropriate tools and technologies to strengthen data governance capabilities.
• Ensure compliance with industry trends, regulatory requirements, and best practices.
• Provide leadership in addressing data challenges, ensuring data supports the company’s growth and innovation.​

Requirements

Academic and Professional Qualifications

• (Essential) Bachelor's Degree in Information Systems, Computer Science, Data Management, Business Administration, or related fields.
• (Preferred) Master’s Degree in Data Science, Information Systems, or Business Analytics with a focus on data governance and strategy.
• (A plus) Professional certifications & additional training:
• Certified Data Management Professional (CDMP)
• Data Governance and Stewardship Professional (DGSP)
• Certified Information Systems Auditor (CISA)
• Certified Information Systems Security Professional (CISSP)
• GDPR or data privacy certifications (e.g., CIPP/E or CIPM)
• Specialized training in metadata management, data quality, and data lineage.
• Courses on compliance, risk management, and regulatory frameworks (e.g., GDPR, CCPA).
• Have 4+ years of experience in data governance, data management, or related fields such as analytics or data quality management.
• Possess prior experience in implementing data governance frameworks, including policy development, metadata management, and data quality initiatives.
• Have knowledge of data governance tools and technologies.
• Exhibit excellent communication, collaboration, and stakeholder engagement skills.
• Show ability to promote data-driven decision-making and foster a culture of data stewardship across teams.
• 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.
• Familiarity with Machine Learning (ML) techniques and Language Learning Models (LLMs) to support data-driven applications.