Job Description

Your IT Future, Delivered

Senior Data Engineer (BI Solutions)

With a global team of 5600+ IT professionals, DHL IT Services connects people and keeps the global economy running by continuously innovating and creating sustainable digital solutions. We work beyond global borders and push boundaries across all dimensions of logistics. You can leave your mark shaping the technology backbone of the biggest logistics company of the world. Our offices in Cyberjaya, Prague, and Chennai have earned #GreatPlaceToWork certification, reflecting our commitment to exceptional employee experiences.

Digitalization. Simply delivered.

At IT Services, we are passionate about Business Intelligence. Our P&P BI Solutions team is continuously expanding. No matter what your level of Data Engineering experience, you can always grow within our diverse and collaborative environment.

#DHL #DHLITServices #GreatPlace #Snowflake #Azure #BusinessIntelligence

Grow together

Role Overview

We are looking for an experienced Senior Data Engineer to join our BI Solutions team. The ideal candidate is a hands-on data engineering professional with strong expertise in cloud-based data platforms, modern data warehousing, and end-to-end data solution delivery.

You will work closely with business stakeholders, product owners, architects, and fellow engineers in an agile environment to design, build, test, and maintain scalable data solutions. As part of a highly collaborative team, each member plays a key role in data architecture, development, quality assurance, and the continuous evolution of our analytics platform.

Key Responsibilities

Data Engineering & Development

• Design, develop, and maintain scalable data solutions using Snowflake and Azure Cloud technologies.
• Build and optimize data pipelines using Azure Data Factory (ADF), Azure Databricks, and DBT.
• Develop and maintain data transformation, integration, and loading processes.
• Implement data models supporting analytics and reporting requirements.
• Ensure data quality, reliability, and performance across the data platform.

Data Quality & Platform Ownership

• Design and execute validation and reconciliation processes to ensure data accuracy.
• Monitor and troubleshoot data pipelines and platform performance.
• Support CI/CD and DevOps practices for data engineering solutions.
• Ensure adherence to data governance, security, and engineering best practices.

Agile Teamwork & Collaboration

• Participate actively in agile ceremonies and continuous improvement initiatives.
• Collaborate closely with business stakeholders to understand and refine requirements.
• Work with architects and engineering teams to deliver scalable and sustainable solutions.
• Communicate proactively with technical and non-technical stakeholders.

Required Skills & Experience

Technical Skills

• Strong hands-on experience with Snowflake and advanced SQL development.
• Experience building cloud-based data solutions on Azure.
• Experience with DBT (Data Build Tool) for transformation and data engineering workflows.
• Strong understanding of data warehousing concepts and best practices.
• Experience in data modeling and scalable data architecture design.
• Good understanding of Data Vault 2.0
• Experience developing ETL/ELT solutions.
• Familiarity with Git, CI/CD pipelines, and DevOps practices.

Data Engineering Focus

• Experience designing and maintaining enterprise data pipelines.
• Ability to perform source-to-target mapping, data validation, and reconciliation activities.
• Understanding of data quality frameworks and operational support processes.
• Experience working with structured and large-scale analytical datasets.

Soft Skills & Mindset

• Strong sense of ownership and accountability.
• Ability to work independently and collaboratively within a global team.
• Proactive mindset with strong analytical and problem-solving skills.
• Excellent communication skills with business and technical stakeholders.

Bonus / Nice-to-Have Skills

• Experience with Azure Data Factory (ADF) and Azure Databricks.
• Experience in data migration and modernization initiatives.
• Knowledge of Power BI or other BI visualization platforms.
• Experience with Python for data engineering or automation.
• Experience working with AI-assisted development tools and productivity solutions.
• Exposure to cloud-native analytics and AI-enabled data platforms.

What We Value

• Engineers who own the data solutions they build and operate.
• Professionals who challenge assumptions, ask questions, and continuously seek improvement.
• A strong engineering mindset focused on quality, reliability, and business value.
• Team players who thrive in a collaborative, fast-paced, and globally distributed environment.
• Individuals who contribute to the modernization of DHL's data and analytics landscape through innovation and technical excellence.

Ready to embark on the journey? Here’s what we are looking for:

As a Senior Data Engineer, having strong experience with Snowflake Database, advanced SQL, Data Warehousing, Data Modeling, and Azure Cloud technologies is essential. Experience with DBT and a good understanding of Data Vault 2.0 will be highly valued.

Hands-on experience with Azure Data Factory (ADF) and Azure Databricks will be considered an advantage.

You are a technology aficionado with a solid understanding of modern data engineering and BI architectures. Experience with data migration and modernization initiatives is highly valued. You are able to work independently, prioritize and organize your tasks under time and workload pressure. Working in a multinational environment, you can expect cross-region collaboration with teams around the globe; therefore, advanced spoken and written English skills will be certainly useful.

An array of benefits for you:

• Hybrid work arrangements to balance in-office collaboration and home flexibility.
• Annual Leave: 42 days off apart from Public / National Holidays.
• Medical Insurance: Self + Spouse + 2 children. An option to opt for Voluntary Parental Insurance (Parents / Parent -in-laws) at a nominal premium covering pre existing disease.
• In House training programs: professional and technical training certifications.