Senior Data Engineer

The HEINEKEN Company; Kraków; On-site; PLN 180,000 - 260,000; Full time

Job summary

HEINEKEN Kraków is seeking a Senior Data Engineer to lead globally, design scalable data products, and collaborate with regional teams to advance analytics, AI, and GenAI initiatives. You will own data models, pipelines, storage strategies, and observability stacks while enabling self-service interfaces for AI engineers and data scientists.

The role requires deep technical expertise, strategic thinking, and the ability to work in a matrixed global organization across Global and Regional teams.

Qualifications

• 7–10 years of experience in data engineering, platform development, and large-scale data systems.

Responsibilities

• Data Platform & Services Engineering: design scalable data pipelines and processing engines for batch, streaming, and event-driven data.
• Data Platform & Services Engineering: architect modular data models and semantic layers for analytics, AI, and self-service.
• Data Platform & Services Engineering: manage orchestration frameworks (Databricks Workflows), compute engines (Spark, SQL, Python).
• Data Quality, Governance & Observability: implement data quality monitoring, lineage, metadata, and anomaly detection.
• Data Quality, Governance & Observability: ensure compliance with GDPR and internal data quality standards.
• Data Quality, Governance & Observability: apply observability with tools like Great Expectations and Monte Carlo.
• Enablement for AI Products: deliver curated datasets and knowledge layers for AI products and LLMs.
• Enablement for AI Products: design pipelines for structured, graph, unstructured data used in ML models.
• Enablement for AI Products: support vector stores, embedding generation, and context retrieval layers.
• Tooling & Self-Service Interfaces: build tooling APIs for data and AI product development and access control.
• Tooling & Self-Service Interfaces: co-design developer platform for pipelines with dbt and Databricks Lakeflow.
• Leadership & Collaboration: mentor data engineering squads and lead design reviews.
• Leadership & Collaboration: collaborate with scientists, PMs, SMEs, and platform teams.

Skills

Leadership

Data engineering

Team mentoring

Cross-functional

English communication

Education

Bachelor's or Master's in CS/Engineering

Tools

Databricks

Spark

SQL

Python

Delta Lake

ADLS

dbt

Databricks Lakeflow

Great Expectations

Monte Carlo

Online Feature Stores

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

Data Platform & Services Engineering

• 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

Leadership & Collaboration

• 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 to speak 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.