Why This Role Stands Out
As a Senior Analytics Engineer at Synapri, you'll drive the development of high-quality data solutions on a modern data platform, gaining significant ownership and impacting critical business decisions. This hybrid role is ideal for experienced Analytics Engineers with expert SQL and PySpark skills, particularly those with Databricks and dimensional modeling experience, who thrive in collaborative environments focused on data excellence. Apply now to shape the future of analytics at Synapri!
Quick Overview
Job Description
Synapri are looking for an experienced Senior Analytics Engineer to play a key role in developing high-quality, analytics-ready data across its modern data platform.
This is an opportunity to take ownership of the curated data layer within a Databricks Lakehouse environment, translating complex business requirements into robust data models and transformation pipelines that support reporting, analytics, and business decision-making.
Key Responsibilities:
- Lead the design and development of curated, analytics-ready dimensional and semantic data models.
- Build, maintain and optimise complex SQL and PySpark transformation pipelines within Databricks.
- Define and maintain KPI definitions, conformed dimensions and consistent business logic across data domains.
- Ensure data quality, integrity, testing, observability and performance across the curated data layer.
- Lead modelling design reviews and contribute to technical and architectural decisions.
- Work closely with Data Architects, BI Developers, analysts and business stakeholders to translate requirements into effective data solutions.
- Establish and promote engineering standards, data governance practices and reusable modelling patterns.
- Contribute to CI/CD pipelines, automated testing frameworks and continuous improvement across the data platform.
Essential Skills:
- Significant experience working as an Analytics Engineer or in a closely related data engineering role.
- Expert-level SQL skills and strong hands-on experience with PySpark.
- Proven experience working with Databricks and Lakehouse architectures.
- Strong understanding of dimensional modelling, including fact tables, dimension tables, star schemas and semantic layers.
- Experience developing curated, analytics-ready datasets for Business Intelligence and analytics consumption.
- Ability to translate complex business requirements into well-structured data models and consistent KPI definitions.
- Strong understanding of data quality, performance optimisation and reliable data transformation practices.
- Experience providing technical leadership, reviewing designs or mentoring other engineers.
Remote (ad-hoc travel to client HQ)
Please apply with a copy of your updated CV for consideration.
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