Total Security Limited is seeking a skilled Data Engineer to play a pivotal role in building and maintaining our data infrastructure, with a specific emphasis on BigQuery as our data warehouse and Looker for business intelligence and reporting. You will be responsible for developing and managing ETL pipelines that seamlessly integrate data from various sources, transforming it into a clean, structured, and easily accessible format. You will also collaborate closely with business and financial analysts to understand their reporting needs, crafting insightful dashboards and reports that empower data-driven decision-making across our subscription based business.

QUALIFICATIONS AND SKILLS:

• Bachelor’s degree in Computer Science, Engineering, or relevant experience.
• 5+ years of experience in data engineering, with a strong focus on ETL and data warehousing.
• Proficiency in SQL and experience working with BigQuery or similar cloud-based data warehouses.
• Hands-on experience with Looker (preferred) or other BI tools
• Familiarity with data pipeline orchestration tools such as Apache Airflow or similar.
• Strong understanding of data modelling principles and best practices.
• Excellent problem-solving and analytical skills.
• Ability to work effectively in a collaborative and fast-paced environment.
• Needs to be a self starter, requiring minimal supervision.

BENEFICIAL EXPERIENCE:

• Experience working in a SaaS or subscription-based business.
• Knowledge of data visualisation techniques and best practices.
• Familiarity with cloud technologies such as GCP (preferred) or AWS.
• GitHub, Python, Java, Unix, HTML

• Data Integration and ETL:
• Design, develop, and maintain robust ETL pipelines, DBT, or similar, ensuring data integrity and accuracy throughout the process.
• Integrate data from diverse sources, including databases, APIs, third-party systems, and SaaS applications, into a centralised BigQuery data warehouse.
• Cleanse, transform, and aggregate data to create a standardised and well-structured data model that supports efficient querying and analysis.
• Data Warehousing and Modelling:
• The team currently uses some filtering in the BQ layer, followed by a business logic layer in Looker (LookML). This facilitates both an ERD layer and a Data Dictionary for the business.
• Collaborate with engineering teams and analysts to design and implement a scalable and optimised data warehouse schema in BigQuery.
• Develop and maintain data models that accurately reflect business requirements and enable efficient data exploration and analysis.
• Optimise data storage and query performance to ensure fast and responsive reporting and analytics.
• Business Intelligence and Reporting:
• Partner with business and financial analysts to understand their reporting and analytics needs, translating them into actionable Looker dashboards and reports.
• Develop visually appealing and user-friendly Looker dashboards that provide insights into key business metrics and performance indicators.
• Create ad-hoc reports and analyses to support strategic decision-making and address specific business questions.
• Data Quality and Governance:
• Implement data quality checks and validation processes to ensure data accuracy and consistency.
• Establish and enforce data governance policies and procedures to maintain data integrity and security.
• Monitor data usage and identify opportunities for optimization and improvement.