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The role
Position Analytics Engineer
Contract type Full Time/Permanent
Reporting to Head of Data
Location London
Overview of role
Zodiac Maritime is undergoing an exciting data transformation, and we're looking for a talented Analytics Engineer to join our growing data team. In this role, you'll be instrumental in supporting the Head of Data in building and deploying robust data infrastructure and analytics solutions using modern data stack (Azure Databricks, ADF and Power BI). You'll bridge the gap between data engineering and analytics, creating scalable data models, automated pipelines, and self-service analytics capabilities that enable data-driven decision making across the organization.
Key Responsibilities And Primary Deliverables
- Data Infrastructure & Pipeline Development: Collaborate with Data Engineer in the design, build, and maintain scalable data pipelines using Azure Data Factory and Databricks to automate data ingestion, transformation, and processing workflows.
- Data Modelling & Architecture: Create and maintain dimensional data models and semantic layers that support business intelligence and analytics use cases.
- Analytics Platform Development: Build and optimize data transformation workflows using dbt, SQL, and Python to create clean, well-documented, and version-controlled analytics code.
- Data Quality Engineering: Implement automated data quality checks, monitoring systems, and alerting mechanisms to ensure data reliability and trustworthiness across the analytics platform, linking issues to the business impact.
- Self-Service Analytics Enablement: Develop reusable data assets, documentation, and tools that enable business users to independently access and analyse data through Power BI and other visualization platforms.
- Collaboration & Requirements Gathering: Work closely with data analysts, and business stakeholders to understand requirements and translate them into technical solutions.
- Documentation & Standards: Create and maintain technical documentation, establish coding standards, and maintain data catalogue to support governance and compliance requirements.
- Mentorship & Knowledge Sharing: Provide technical guidance to junior team members and promote best practices in analytics engineering across the organization.
Skills profile
- 5+ years working experience in data engineering, analytics engineering, or related technical roles with strong focus on building transformation workflows and analytics infrastructure.
- Advanced technical proficiency in SQL, Python, and modern data transformation tools (dbt strongly preferred), with experience in cloud data platforms (Azure Databricks, Snowflake, or similar).
- Proven experience designing and implementing scalable data architectures, including dimensional modelling, data lakehouse / warehouse concepts, and modern data stack technologies.
- Strong software engineering practices including version control (Git), CI/CD pipelines, code testing, and infrastructure as code principles.
- Deep understanding of data quality frameworks, data governance principles, and experience implementing automated monitoring and alerting systems.
- Analytics platform expertise with hands-on experience in business intelligence tools (Power BI, Tableau, Looker) and understanding of self-service analytics principles.
- Strong problem-solving abilities with experience troubleshooting complex data issues, optimizing performance, and implementing scalable solutions.
- Excellent communication skills with ability to translate technical concepts to non-technical stakeholders and collaborate effectively with cross-functional teams.
- Experience working in agile environments with ability to manage multiple priorities, work independently, and deliver high-quality solutions within established timelines.
- Curiosity and continuous learning mindset with enthusiasm for exploring new technologies and best practices in the rapidly evolving analytics engineering space.
