About StarCompliance
StarCompliance is on a mission to make compliance simple and easy. Trusted globally by enterprise financial institutions, the user-friendly STAR platform empowers organizations to achieve regulatory compliance while safeguarding their integrity and business reputations. Through a customizable, 360-degree view of employee activity, the STAR software enables firms to automate the detection and resolution of potential areas of conflict while streamlining daily workflows and increasing efficiency.
Role
We are seeking a Data & Analytics Engineer to join our existing Data team, helping bridge the gap between data engineering, analytics engineering, and business intelligence. This hybrid role is ideal for someone who is equally comfortable building scalable data platforms and pipelines as they are designing semantic models and insightful dashboards for end users.
You will play a key role in enhancing our external Data Analytics platform, delivering high-quality data products, dashboards, and analytics capabilities to thousands of users across hundreds of clients globally. You will be responsible for ensuring data is accurate, scalable, well-structured, and ready for consumption within Snowflake, while also delivering intuitive visualizations that support customer and internal decision-making.
Our platform utilises a modern cloud-based tech stack featuring Microsoft Azure, Snowflake, and ThoughtSpot, alongside in-house data ingestion and automation tooling. The team embraces modern engineering practices, CI/CD pipelines, Agile methodologies, and emerging AI-assisted development tooling.
We are looking for individuals who challenge ideas respectfully in pursuit of better outcomes. You should be passionate about data, take pride in your work, and proactively drive tasks forward while balancing technical excellence with customer impact.
- Design, build, and maintain scalable, efficient, and fault-tolerant data pipelines and products using Azure and Snowflake technologies
- Design and maintain dimensional data models and semantic layers for downstream analytics and reporting
- Develop and maintain embedded analytics dashboards and reporting solutions using ThoughtSpot and related BI technologies
- Write efficient, performant, and optimized SQL queries to support analytics and operational reporting requirements
- Collaborate closely with stakeholders, customers, engineers, and product teams to gather requirements and translate them into data solutions and dashboards
- Ensure data platforms, dashboards, and reporting solutions are secure, monitored, scalable, and performant
- Investigate and resolve data quality, pipeline, and reporting issues across the analytics platform
- Contribute to code reviews, engineering best practices, and continual improvements across the data platform
- Contribute to data governance, observability, and quality initiatives
- Run technical spikes and proof-of-concepts for emerging technologies and share findings with the wider team
- Support CI/CD processes, deployment pipelines, and Git-based development workflows
- Participate actively in Agile ceremonies, backlog refinement, estimations, and technical debt management
- Act as a bridge between technical teams and business stakeholders, clearly communicating technical concepts to non-technical audiences
- Experience in data engineering and/or analytics engineering within fast-paced, large-scale production environments
- Strong proficiency in SQL, including performant query design and relational database concepts
- Experience designing data models using dimensional modelling techniques and star schemas
- Experience building and maintaining production data pipelines and cloud-based data platforms
- Experience with Snowflake and Microsoft Azure technologies
- Proven experience developing dashboards and reports using ThoughtSpot, Power BI, or similar BI platforms
- Familiarity with ETL/ELT processes, data warehousing concepts, and modern data architecture patterns
- Experience with CI/CD processes, Azure DevOps, Git, and deployment pipelines
- Experience with scripting or programming languages such as Python, PowerShell, or C#
- Familiarity with harnessing AI-assisted tooling to deliver faster, higher-quality data services (e.g. Cursor, Claude)
- Strong communication, collaboration, and problem-solving skills
- Comfortable working within Agile development environments
- Experience with SnowSQL and advanced Snowflake capabilities
- Experience deploying data products or analytics solutions to external customers
- Experience within the financial services industry
- Knowledge of data governance, data quality, observability, and data security principles
- Experience with tools such as Mend and SonarQube
- Azure, Snowflake, ThoughtSpot, or Power BI certifications
- Experience working with embedded analytics products and customer-facing reporting platforms
StarCompliance Background Checks
All positions require pre-employment screening due to employees potentially having access to highly sensitive and confidential information involving finance and compliance; candidates must be trustworthy and have a heightened sensitivity to protecting confidential financial, professional information. To be eligible for employment with StarCompliance, candidates must undergo a rigorous background investigation with checks including, but not limited to, criminal record history, consumer credit, employment history, qualifications, and education checks.
Equal Opportunity Employer Statement
We prohibit discrimination and harassment of any kind based on race, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, gender identity or expression, marital/civil union/domestic partnership status, veteran status or any other protected characteristic as outlined by country, state, or local laws.
This policy applies to all employment practices within our organisation, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. StarCompliance makes hiring decisions based solely on qualifications, merit, and business needs at the time. For more information, please request a copy of our Equal Opportunities Policy.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
