Senior Data Engineer

Employee Status

Regular : Indefinite

Job Type

Permanent

Job Level

Senior Expert

Location

Hungary-Budapest-Dombóvári út 28.

Senior Data Engineer

About Digital Factory

It’s a place where the agility of a start-up meets the stability of a global powerhouse!

Be part of our journey as we transform from a traditional fuel retailer to a cutting-edge, digitally driven consumer goods and mobility services provider. As part of MOL Group’s 2030 - Enter Tomorrow strategy, our mission is to lead the market in Central Europe through innovative digital transformation.

At Digital Factory , we harness the power of data to drive business decisions by building a comprehensive Data Lake and developing advanced analytics solutions in forecasting, category management, pricing, and workforce optimization. We're also revolutionizing customer experience with , our new digital, app-first loyalty rewards program on the , designed to personalize and enhance convenience for our customers.

MOL Group Consumer Services are currently serving approx. 10 million customers through 2,000 service stations across 9 countries, which provides an excellent scale to leverage our technologies regionally.

Our engineers are innovators with a passion for business, user behavior, and data. They excel in communication, build strong relationships with non-engineers, and navigate product / engineering tradeoffs with ease. With a focus on quick product validation and end-to-end feature ownership, they drive continuous learning and impactful solutions.

If you're curious, proactive, and eager to make a difference, the Digital Factory's Engineering Team is the place for you!

About the Role

We are looking to hire an experienced and passionate Senior Data Engineer to join Digital Factory. The new team member is part of our digital engineering team, and the focus of this role is on leveraging MS SQL and Databricks' capabilities for data engineering, analytics , and machine learning in a cloud-native environment.

Main Responsibilities

• Build scalable ETL / ELT pipelines using Azure Databricks to integrate data sources like Azure Blob Storage, Azure Data Lake, and SQL Databases.
• Automate data workflows, including ingestion, transformation, and loading processes, using Azure Data Factory (ADF), Databricks workflows, and Azure Functions.
• Implement real-time streaming data pipelines with Databricks Structured Streaming for IoT or event-driven architectures.
• Use Apache Spark in Databricks for efficient data cleaning, transformation, and enrichment of large datasets.
• Design and implement dimensional data models (e.g., star schema) for optimized performance in Azure Synapse Analytics.
• Leverage Delta Lake for ACID-compliant data storage and optimization for batch and stream processing.
• Tune Databricks notebooks and jobs for performance, utilizing autoscaling and optimizing Spark configurations.
• Apply data partitioning, manage table storage formats (e.g., Parquet, Delta), and index data for faster querying.
• Manage Databricks clusters, ensuring resource efficiency through autoscaling, sizing, and cost management.
• Integrate Databricks with Azure services such as Azure Data Lake Storage, Azure SQL, Azure Synapse, Azure Key Vault, and Power BI.
• Set up monitoring, alerting, and logging for data pipelines using Azure Monitor, Databricks Jobs, and Azure Log Analytics.
• Ensure data security through encryption, role-based access control (RBAC), Azure Active Directory (AAD), and Databricks Secrets.
• Implement data quality checks in Databricks pipelines to ensure data accuracy and consistency.
• Use Git for version control and implement CI / CD pipelines for Databricks workflows via Azure DevOps.
• Collaborate with data scientists, analysts, and business users to deliver data-driven insights and solutions.
• Maintain documentation of data architectures, processes, and pipelines in DF Confluence for scalability and collaboration.
• Support exploratory data analysis and integrate Databricks with Power BI or other visualization tools.
• Collaborate with data science teams to deploy machine learning models using Databricks MLflow and Azure ML services

About Your Experience and Skills

University or college degree with specialization in Computer Science or Information Systems or equivalent

5+ years of experience in DWH Development, Data Engineering

Agile DevOps (strategies, processes, and tooling)

Proven analytical abilities

What We Offer

How to apply?

If you wish to form the future with us, please submit your applications via our career site :

Main Recruitment Steps

If you would like to know more about Digital Factory : digitalfactory.info

Meet your Hiring Manager : Zsolt Horváth (https : / / www.linkedin.com / in / hozso / )

At MOL Group, we know that our strength lies in diversity. During the selection process, we provide equal opportunities to all applicants with the appropriate qualifications and work experience, regardless of age, gender, disability, or reduced work capacity, sexual orientation, or ethnicity. At MOL Group, everyone matters.

If you have any specific needs related to your reduced work capacity at any stage of the recruitment process, please inform our recruitment team! We are happy to assist.