Analytics Engineer

Relevant experience required (in years):6+ years of total exp with minimum 3 years as an Analytics Engineer or in a similar role.

Your department:

As Analytics Engineer within the Enabling Functions department of Vanderlande you support Finance, HR, and IT by delivering robust, scalable, and future-ready data solutions. Our mission is to empower these departments with high-quality, governed data products that drive operational excellence and strategic decision-making.

At the core of our work is the Vanderlande Data Platform, a cloud-native solution built on Azure and aligned with Data Mesh principles. This platform enables us to ingest, transform, and enrich data from diverse source systems, creating trusted, reusable data assets tailored to the needs of our Enabling Functions stakeholders.

At the heart of our efforts lies the Data Platform, the core product we are diligently enhancing. This Azure cloud enabled platform based on the Data Mesh principle empowers us to deliver valuable Data Products by transforming, processing, combining, and enriching data from various source systems, ultimately creating a reliable source of truth for our customers.

By utilizing advanced analytics techniques and the latest technology, our focus on innovation empowers us to continuously improve and innovate.

Operating as a scaled Agile organization, we embrace the SAFe Agile framework and work collaboratively across different teams, all united by a common backlog and shared roadmap. This approach allows us to be highly adaptable, continuously adjusting to the evolving strategic needs of stakeholders within Vanderlande.

Responsibilities:

As an Analytics Engineer at Vanderlande you'll be at the forefront of driving data-driven solutions and shaping the future of our organization by working on the data platform. Your key responsibilities will involve translating business needs into functional requirements, designing and developing data products, pipelines, and reports, and analyzing data to solve use cases resulting in optimized business processes and fact-based decision-making.

As being part of a cross functional full-stack team, together with your colleagues you are responsible for the creation and delivery of an end-to-end solution to our business stakeholders. In this role, you are a tech-savvy, action-oriented, and collaborative colleague who can wear multiple hats - part Data Engineer, - part Data Analyst and even though you have an area of expertise, you can fulfil each of those roles up to a certain point.

On a day-to-day basis, you will focus on creating and maintaining data products, data pipelines using Python, PySpark and SQL, and dashboards using tools like Qlik, or Power BI. Working in an Agile environment, proactively contributes to scrum events ensuring seamless coordination with the team and swift adaptability to changing priorities. They thrive in a fast-paced, iterative development environment, where constant feedback and continuous improvement are key.

In this role, you:

• Translate business needs into functional requirements providing essential information on business use cases.

• Translate functional requirements into thorough and feasible data products, analytics solutions and dynamic dashboards;

• Utilize Python, PySpark, SQL, or R for data retrieval and manipulation.

• Develop, test, and maintain data products, pipelines by the use of the Azure stack and Databricks, ensuring data reliability and quality.

• Design and implement architectures for efficient data extraction and transformation.

• Work on creating and maintaining landing zones in the data platform.

• Actively participate in and contribute to Continuous Integration and Continuous Deployment (CI/CD) practices, ensuring smooth and efficient development and deployment processes within the data platform

• Integrate data pipelines and reports into testing frameworks, allowing for rigorous performance testing and validation to ensure seamless performance.

• Monitor and maintain data pipeline stability, offering support when required.

• Analyze, interpret, and visualize data to drive business process optimization and fact-based decision-making.

• Create, deploy, and maintain interactive dashboards and visualizations using Qlik or Power BI.

• Perform a comprehensive analysis and proactively implement solutions to assess and enhance data quality and data reliability.

• You are eager to improve yourself and strive for continuous enhancement of processes and development of our data products.

• Stay updated with the latest developments in the analytics field and share knowledge with the team.

Your Qualification and Skills:

If youre an experienced, enthusiastic and versatile Analytics Engineer, you will bring:

• Minimum bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).
• 6+ yrs of total exp with min 3 years of prior experience working as an Analytics Engineer or in a similar role .
• Ability to work effectively as part of a cross-functional international full stack team, collaborating with other developers, and stakeholders.
• Experience in writing code in Python, PySpark, SQL, or R for data retrieval and manipulation is a strong preference.
• Demonstrated experience and proficiency in working with Azure Stack and Databricks is required for this role.
• Proficiency or interest in using DevOps practices and tools for continuous integration, continuous delivery (CI/CD), and automated deployment of data products and data pipelines
• Strong communication skills to effectively convey complex technical concepts in a clear and understandable manner to both technical and non-technical stakeholders.
• Enthusiastic, proactive, driven, and actively seeking opportunities for personal development and growth.
• Demonstrated curiosity and commitment to staying updated with the latest trends, tools, and best practices in the data & analytics field.
• Familiar with agile methodologies and thrives in its dynamic and collaborative environment.
• Knowledge of visualization tools like Power BI or Qlik is plus.