Analytics Engineer

Zodiac Maritime Ltd; London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading maritime company in London seeks an Analytics Engineer to support their data transformation efforts. The role involves building and maintaining data infrastructure and analytics solutions using tools like Azure Databricks and Power BI. The ideal candidate has over 5 years of experience in data engineering and a strong technical background in SQL and Python. This position offers a full-time, permanent contract with opportunities for mentorship and knowledge sharing.

Qualifications

• 5+ years in data engineering or analytics engineering with a focus on workflows.
• Proficiency in SQL, Python, and modern transformation tools.
• Experience in designing scalable data architectures.

Responsibilities

• Collaborate on data pipeline development using Azure Data Factory.
• Create dimensional data models for analytics use cases.
• Build and optimize data transformation workflows.

Skills

SQL

Python

Data transformation tools (dbt preferred)

Business intelligence tools (Power BI)

Data quality frameworks

Agile environments

Tools

Azure Databricks

Azure Data Factory

Version control (Git)

Job description

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.