Senior Data Engineer

Heineken; Kraków; On-site; PLN 180,000 - 280,000; Full time

Job summary

HEINEKEN Kraków is seeking a Senior Data Engineer to lead global data engineering initiatives, design scalable data models, and build self-service interfaces for AI engineers and data scientists.

The role focuses on orchestration, data governance, and toolchains like Databricks and Delta Lake, with a strong emphasis on collaboration across Global and Regional teams in a dynamic, global beer company.

Qualifications

• 7-10 years of experience in data engineering, platform development, and/or large-scale data systems.
• Proven leadership of engineering teams.
• Strong hands-on knowledge of modern data platforms such as Databricks.
• Experience with data pipeline orchestration, data modeling, data quality frameworks, and observability stacks.
• Familiarity with unstructured data processing and GenAI enablement pipelines is highly desirable.
• Comfortable working in a matrixed global organization with both Global and Regional teams.

Responsibilities

• contributing to the design and implementation of scalable data pipelines, ingestion frameworks, and processing engines for batch, streaming, and event-driven data
• architecting and maintaining modular data models and semantic layers optimized for analytics, AI, and self-service exploration
• defining and managing orchestration frameworks, such as Databricks Workflows, compute engines, including Spark, SQL, and Python, and storage strategies, including Delta Lake, ADLS, and Online Feature Stores.
• Data Quality, Governance & Observability: establishing robust data quality monitoring, lineage tracking, metadata management, and anomaly detection processes
• collaborating with data management and governance teams to ensure GDPR compliance
• implementing observability standards using tools such as Great Expectations and Monte Carlo
• Enablement for AI Products: delivering curated datasets and domain-specific knowledge layers for traditional AI products and agentic AI applications
• designing pipelines that process and enrich structured, graph, and unstructured data, including text, documents, and images, used in ML models and by LLMs or RAG-based systems
• partnering with AI Engineering teams to support vector stores, embedding generation, and context retrieval layers
• defining tooling frameworks and APIs for data and AI product development, monitoring, and access control
• co-designing and managing a developer platform for developing and deploying data pipelines using dbt and Databricks Lakeflow
• promoting the reuse of data services across domains through clear documentation, data lineage, templates, data contracts, and support.
• managing and mentoring data engineering squads, leading technical design reviews, and providing coaching
• collaborating cross-functionally with Data Scientists, ML and AI Engineers, Product Owners, Business SMEs, and Platform teams
• contributing to the global data engineering vision, architecture principles, and capability roadmap.

Skills

Data engineering

Databricks

Data pipelines

Leadership

Observability

GenAI

Unstructured data

SQL

Python

Tools

Delta Lake

ADLS

Great Expectations

Monte Carlo

dbt

Databricks Lakeflow

Job description

Digital & Technology Team (D&T) is an integral division of HEINEKEN Business Services Poland (HBSP). We are committed to making Heineken the most connected brewery in the world. That includes digitalizing and integrating our processes, ensuring best-in-class technology, and embedding a data-driven culture. By joining us, you will work on one of the most dynamic and innovative teams and directly help shape the future of Heineken.

Would you like to meet the Team, see our office, and much more? Visit our website: Heineken (https://heineken-dt.pl/ )

The Senior Data Engineer is accountable for leading globally and collaborating with regional data engineering teams to design, deliver, and continuously improve high-quality, scalable, and reusable enterprise data products and services. These services form the backbone of analytics, AI, and GenAI initiatives across global business domains. You will own the design and engineering of data models, orchestration pipelines, storage strategies, compute environments, and observability stacks—with a strong focus on self-service interfaces for AI engineers, analysts, and data scientists. This role requires combining deep technical expertise with strategic thinking, including support for feature engineering, unstructured data, and GenAI use cases.

Your responsibilities would include:

contributing to the design and implementation of scalable data pipelines, ingestion frameworks, and processing engines for batch, streaming, and event-driven data

architecting and maintaining modular data models and semantic layers optimized for analytics, AI, and self-service exploration

defining and managing orchestration frameworks, such as Databricks Workflows, compute engines, including Spark, SQL, and Python, and storage strategies, including Delta Lake, ADLS, and Online Feature Stores.

Data Quality, Governance & Observability

establishing robust data quality monitoring, lineage tracking, metadata management, and anomaly detection processes

collaborating with data management and governance teams to ensure compliance with global data policies, including GDPR and internal data quality standards

implementing observability standards using tools and platforms such as Great Expectations and Monte Carlo.

Enablement for AI Products

delivering curated datasets and domain-specific knowledge layers for traditional AI products and agentic AI applications

designing pipelines that process and enrich structured, graph, and unstructured data, including text, documents, and images, used in ML models and by LLMs or RAG-based systems

partnering with AI Engineering teams to support vector stores, embedding generation, and context retrieval layers.

Tooling & Self-Service Interfaces

defining and implementing tooling frameworks and APIs for data and AI product development, monitoring, and access control

co-designing and managing a developer platform for developing and deploying data pipelines using tools and frameworks such as dbt and Databricks Lakeflow

promoting the reuse of data services across domains through clear documentation, data lineage, templates, data contracts, and support.

managing and mentoring data engineering squads, leading technical design reviews, and providing coaching

collaborating cross-functionally with Data Scientists, ML and AI Engineers, Product Owners, Business SMEs, and Platform teams

contributing to the global data engineering vision, architecture principles, and capability roadmap.

You are a good candidate if you have:

• 7-10 years of experience in data engineering, platform development, and/or large-scale data systems
• Proven leadership of engineering teams
• Strong hands-on knowledge of modern data platforms such as Databricks
• Experience with data pipeline orchestration, data modeling, data quality frameworks, and observability stacks
• Familiarity with unstructured data processing and GenAI enablement pipelines is highly desirable
• Comfortable working in a matrixed global organization with both Global and Regional teams.

At HEINEKEN Kraków, we take integrity and ethical conduct seriously. If someone has concerns about a possible violation of legal regulations indicated in the Polish Whistleblowing Act or our Code of Business Conduct, we encourage them tospeak up . Cases can be reported to the global team or locally (in line with the local HGSS Whistleblowing procedure) by selecting the proper option in this tool or by communicating it on the hotline. #LI-HYBRID