ICT Data Engineer

Responsibilities

• Assemble large, complex data sets to meet both functional and non-functional business requirements.
• Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming substantial volumes of structured and unstructured data.
• Develop robust ETL processes to integrate data from diverse sources.
• Identify and implement internal process improvements, including infrastructure redesigns for greater scalability, improved data delivery, and automation of manual tasks.
• Build the required infrastructure for efficient extraction, transformation, and loading from multiple data sources using AWS, Azure, DB2, and SQL technologies.
• Create scalable tables to provide actionable insights into key business performance metrics such as operational efficiency and customer acquisition.
• Collaborate with stakeholders including Data Product teams to support data infrastructure needs and address data-related technical issues.
• Design and maintain data models, schemas, and database structures to support analytical and operational use cases.
• Optimize data storage and retrieval mechanisms for performance and scalability.
• Lead and coordinate cross-functional AI programs from concept to deployment, ensuring alignment with business goals and timelines.
• Work with data scientists, engineers, and business stakeholders to define and prioritize program objectives.
• Apply statistical analysis and machine learning techniques to solve business and operational problems.
• Translate business requirements into analytical solutions and AI use cases, partnering with stakeholders to ensure alignment.
• Build and deploy predictive models to forecast warranty claims, failure rates, and cost trends.
• Ensure data quality, lineage, documentation, and governance compliance.
• Create dashboards and analytical outputs that drive adoption and operational impact.
• Collaborate with business data engineers and platform teams on scalability, performance, and best practices.

Requirements

• Bachelor's degree in Data Science, Statistics, Engineering, Computer Science, or a related field.
• Minimum of 3 years of experience as a Data Scientist, Advanced Analyst, or similar role.
• Strong proficiency in Python, SQL, PySpark, and visualization tools such as Power BI or Foundry Workshop.
• Solid understanding of statistics, exploratory data analysis, and applied machine learning.
• Experience working with large, complex datasets in enterprise environments.
• Ability to communicate analytical findings clearly to both technical and non-technical audiences.
• Proven experience delivering end-to-end analytics or data science solutions into production.
• Experience with one or two data and cloud platforms such as Palantir Foundry, Snowflake, Databricks on AWS/Azure/GCP.
• Strong communication and stakeholder engagement skills.

Technologies

• Python, SQL, PySpark
• Power BI, Foundry Workshop
• AWS, Azure
• DB2, Palantir Foundry, Snowflake
• Databricks, GCP

Preferred Qualifications

• Familiarity with data modeling, semantic layers, and enterprise data platforms.
• Automotive and manufacturing industry experience.
• Exposure to MLOps concepts, model deployment, or monitoring.
• Hands-on experience with Palantir Foundry and Snowflake Intelligence.
• Master’s degree in Data Science, Statistics, Engineering, Computer Science, or a related field.
• Comfort working in a fast-paced environment that emphasizes rapid delivery, collaboration, and value generation.