Data Engineering

Our team of data experts deep dive into structuring, modelling, automation, repeatability, security, and interoperability of data. Creating robust data pipelines built on open standards and formats, and building the infrastructure and platforms so you can easily access your data, and data science and analysis teams can focus on what they do best.

Solid technical foundations are the key to realising your data strategy. By working with Pivotl you’ll reap the rewards of long lasting data engineering solutions and capabilities that will transform the effectiveness and speed of decision making across your organisation.

You’ll benefit from our extensive expertise delivering cloud native data pipelines using short feedback loops with embedded quality and security (DataOps); reducing development, time and ongoing support costs.

Sources & Ingestion

Your data assets are everywhere and to make use of them you need to understand where your data sources are, what data they contain, and how they can be accessed.

Our robust data infrastructure and pipelines allow you to access data from external, third-party systems, production systems, and real-time information from sensors and devices, which you can process, manage and utilise for downstream processing.

Your raw data will be ingested into a single platform or system – a data warehouse, data lake or lake house where it is processed, transformed and utilised for analytics, data science, or machine learning activities.

Pipelines & Transformation

Transporting your data from source systems to its destination requires orchestration via a pipeline architecture that utilises systems, code or interfaces to copy, cleanse, and transform raw data into a format that makes it useful in a target storage solution such as a data warehouse or data lake. And ultimately into a useful format that people and machines can access and understand.

Pipelines are critical to the success of your data initiatives and we apply robust, high-quality engineering practices to ensure they work as intended.


Data comes in many shapes, sizes, and formats from structured and semi-structured to unstructured, and you need your storage solutions to be flexible and un-coupled from processing power to support scaling as your data grows.

Our data platforms use architectural designs that leverage the combined strengths of data warehousing and data lakes with none of the downsides, providing the basis of your data management needs.