Lead Data Engineer: AI-Ready Data Platform & Analytics

Huntsman; Kraków; On-site; PLN 200,000 - 350,000; Full time

Job summary

Huntsman seeks a Lead Data Engineer to design, develop and evolve an enterprise data platform. You will drive scalable data warehouses and data lakes, build high-performance ETL/ELT pipelines, and lead data governance across the organization.

You will mentor engineers, partner with stakeholders, and enable AI-ready analytics and digital innovation while ensuring robust data security and compliance.

Qualifications

• Bachelor's degree in IT Engineering, Information systems, Analytics, or a related field.
• Master's degree preferred.
• 10+ years in Data engineering, Data Warehousing, Analytics Engineering, or related fields.
• Proven experience designing, building, and operating enterprise-scale data warehouse and data platform solutions.
• Strong expertise in SQL, Python, data modelling, ETL/ELT development, and data warehouse architecture.
• Hands-on experience with Databricks / DatabricksApps, PySpark, Datalake architecture, API development, Git & DevOps Knowledge of Azure Data Platform, Azure Data Factory, machine learning enablement, data security and governance, compliance requirements, and reporting solutions such as Power BI.
• Demonstrated success delivering large-scale data transformation initiatives.
• Ability to translate business requirements into scalable, data-driven solutions.
• Strong analytical and problem-solving skills, with a passion for leveraging data to drive business value.
• Excellent interpersonal skills, with the ability to collaborate across functions and effectively communicate insights to a multicultural audience.
• Knowledge of Supply Chain processes and ERP/SAP environments is considered an advantage.

Responsibilities

• As a Lead Data Engineer, you will be responsible for:
• Building and maintaining scalable enterprise data warehouses, data lakes, and monitoring applications
• Driving migration from legacy data model
• Designing, developing and maintaining high-performance ETL/ELT pipelines using Databricks, SQL, Python, and PySpark.
• Integrating, transforming, and standardizing data from multiple business functions and divisions, including Supply Chain, Finance, Sales, Marketing and other enterprise systems.
• Developing and optimizing batch, near real-time, and real-time data processing solutions to meet business and operational needs.
• Providing leadership to the organization in the Databricks environment
• Enabling advanced analytics, scenario planning, intelligent automation and AI-driven use cases by delivering scalable and well-governed data solutions.
• Providing technical leadership and mentoring to data engineers and other technical team members while contributing hands-on to key development activities.
• Defining and promoting data engineering best practices, development standards, and technical guidelines to support sustainable platform growth.
• Partnering with business leaders, process owners and technology teams to understand requirements and deliver strategic data initiatives that drive business value.
• Acting as key contributor in Huntsman's data transformation journey helping shape the future enterprise data landscape and supporting the organization's long-term digital ambitions.

Skills

SQL

Python

Data modelling

ETL/ELT development

Data warehouse architecture

Leadership

Mentoring

Communication

Problem solving

Education

Bachelor's degree in IT Engineering/Information systems/Analytics

Master's degree preferred

10+ years in Data engineering/Data Warehousing/Analytics Engineering

Tools

Databricks

DatabricksApps

PySpark

Datalake architecture

API development

Git

DevOps

Azure Data Platform

Azure Data Factory

Power BI

Job description

Huntsman seeks a Lead Data Engineer to design, develop and evolve an enterprise data platform. You will drive scalable data warehouses and data lakes, build high-performance ETL/ELT pipelines, and lead data governance across the organization.

You will mentor engineers, partner with stakeholders, and enable AI-ready analytics and digital innovation while ensuring robust data security and compliance.