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Analytics Engineering

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Engineer scalable data models that drive real business decisions.

Analytics Engineers bridge data engineering and business impact. You work closely with Data Engineers and BI professionals to design scalable data models and enable reliable, data-driven decision-making across the organization.

You take ownership of data modeling, building trusted datasets and powering dashboards that drive real business outcomes. By transforming raw data into structured, well-modeled data products, you ensure consistency, quality and usability. To achieve this, you design and maintain automated pipelines that make high-quality data continuously available for reporting and analysis.

Technical alignment phase

Every Analytics Engineer starts with a focused two-week engineering alignment phase. This intensive period strengthens advanced SQL, scalable data modeling, and building reliable data pipelines that enable trustworthy, business-ready insights. You deepen your understanding of data quality frameworks, testing practices and modern analytics engineering standards.

Rather than classroom-style learning, you work hands-on through realistic engineering challenges and production-like scenarios. Our Analytics Engineering Lead tailors the approach to your background to ensure a strong and consistent technical baseline before stepping into complex, real-world data environments.

The first 12-months

After the alignment phase, you join one of our partner organizations four days a week, embedded in a real data team. On the fifth day, you return to Xccelerated in Amsterdam for advanced deep-dives, architecture discussions and technical sparring. These sessions focus directly on the challenges within your client project, while deepening your expertise in modern data warehouse architectures, advanced modeling frameworks and scalable data processing practices. At the end of the year, you transition into a permanent role at the partner organization.

Technical focus areas

  • Production-grade Data Engineering with Python & Scala

  • Deploying and operationalizing Machine Learning models

  • Distributed data processing with Kafka and Spark

  • Workflow orchestration with Apache Airflow

  • Containerization and runtime environments with Docker

  • Data storage architectures, lakes and lakehouses

  • Distributed Systems design principles

  • Cloud-native data platform engineering

  • Engineering leadership and communication

  • Professional growth and impact development

Explore the complete technical structure. Download the full overview!

Why work at Xccelerated?

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Technical acceleration

Work with senior Tech Leads on analytics architecture, scalable data modeling, modern warehouse patterns and CI/CD for analytics workflows. We don’t revisit fundamentals. We sharpen how you design, structure and deliver trusted data products.

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Real production impact

You work in complex data environments, contributing to modern analytics platforms, scalable data models and high-impact business use cases. No theoretical exercises. No isolated dashboards. Just trusted data products that drive decisions at scale.

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Like-minded professionals

Work in an international environment with like-minded professionals who are on the same page: learning, making impact, sharing knowledge and having fun.

 

Ready to deepen your impact as an Analytics Engineer?

As an Analytics Engineer at Xccelerated, you work alongside experienced engineers on complex, high-impact projects for leading organizations. You contribute directly to modern analytics platforms and help turn data into trusted, decision-ready products at scale.

You design, build and maintain scalable data models and analytics workflows. You care about clean modeling standards, data quality and delivering reliable, well-structured data that enables teams to make confident business decisions.

  • A technical bachelor’s or master’s degree (e.g. Computer Science, Data Science, Informatics or related field)

  • 3–5 years of experience as an Analytics Engineer, BI Developer or Data Analyst in a production environment

  • Strong experience with data modeling (e.g. dimensional modeling, star schema, DBT) and building trusted datasets

  • Advanced SQL skills; experience with Python is a strong plus

  • Experience with at least one major cloud platform (Azure, GCP or AWS) and modern data warehouse tooling

If you have any questions, please contact Samantha, our Talent acquisition lead, through sgoncalves@xccelerated.io or telephone number 0613889770