Simple Machines. Data Engineered to Life™ 

Simple Machines is a leading independent boutique technology firm with a global presence, including teams in London, Sydney, San Francisco, and New Zealand. We specialise in creating technology solutions at the intersection of data, AI, machine learning, data engineering, and software engineering. Our mission is to help enterprises, technology companies, and governments better connect with and understand their organisations, their people, their customers, and citizens. We are a team of creative engineers and technologists dedicated to unleashing the potential of data in new and impactful ways. We design and build bespoke data platforms and unique software products, create and deploy intelligent systems, and bring engineering expertise to life by transforming data into actionable insights and tangible outcomes. We engineer data to life™. 

The Role: 

 
At Simple Machines, our Senior Analytics Engineers play a pivotal role in delivering expert consulting services to our clients. They are instrumental in crafting scalable ETL frameworks and developing modern data pipelines, as well as creating reusable data products that drive significant business value. Utilising their deep knowledge in SQL, Python, and platforms such as Snowflake, AWS, and Google Cloud, they are key to our mission to unlock the potential of each of our clients’ data. 

Technical Responsibilities:

• Advanced Data Product Engineering: Spearhead the development of complex data products using SQL, with an emphasis on quality, scalability and performance. Use tools such as dbt for efficient data transformations and Google DataFlow for processing both streams and batch data. Integrate additional tools such as Apache Beam for handling complex data processing patterns that require both batch and real-time processing capabilities. 
• Modern Data Stack Integration: Seamlessly integrate components of the Modern Data Stack into project workflows, utilising Snowflake and BigQuery for data warehousing. Incorporate tools such as Fivetran and Stitch for data integration. 
• Data Pipeline Optimisation: Design, build, and optimise ETL processes using Apache Airflow and dbt to streamline data integration and workflow efficiency. Implement Kafka for building robust real-time data streaming capabilities, and ensure that data pipelines are equipped to handle high-volume, high-velocity data from diverse sources while maintaining accuracy and reliability. 
• Strategic Data Storage Solutions: Manage and optimise data storage and compute resources across cloud platforms like AWS, Google Cloud, and Microsoft Azure. Utilise technologies such as AWS Redshift for data warehousing and Azure Blob Storage for scalable cloud storage solutions, focusing on cost-effectiveness and performance optimisation. 
• Robust Security and Compliance Frameworks: Maintain strict data security and compliance standards across all data platforms and integrations. Implement industry best practices in data governance with tools like Collibra for data governance and Catalog & CockroachDB for geo-replicated, transactional databases, ensuring the protection of sensitive data and compliance with global data protection regulations (e.g., GDPR). 

Consulting Responsibilities:

• Client Advisory: Work closely with internal stakeholders to refine data requirements, ensuring that analytics solutions are perfectly aligned with the strategic business objectives. This role involves a consultative approach to understanding and addressing key business challenges through effective data strategies. 
• Collaborative Project Execution: Assist the project lead in managing and executing analytics projects, ensuring active participation from all team members. This role involves facilitating teamwork to meet project deadlines and achieve desired outcomes, fostering a collaborative environment that encourages sharing of ideas and expertise across the team. 
• Training and Empowerment: Provide training and support to business users and data scientists, enabling them to effectively access and leverage new data products. Focus on enhancing data literacy within the organisation by developing comprehensive educational materials and workshops that promote a deeper understanding of data capabilities and applications. 

Requirements

Ideal Skills and Experience:

• Essential Data Handling Abilities: Highly proficient in SQL and Python, with solid experience in ETL frameworks like Apache Airflow and the data build tool (dbt). 
• Expertise in Cloud Data Management: Adept in managing extensive data sets using cloud data warehouses such as AWS Redshift, Google BigQuery, and various data lake technologies. 
• Data Modelling and Warehousing Acumen: Comprehensive understanding of data modelling concepts with practical experience in data warehousing systems like Snowflake. 
• Data Product Development: Experience or understanding of the creation and management of data products that adhere to data mesh principles. 
• Analytics and Visualisation Proficiency: Skilled in utilising analytics and visualisation tools like Looker, Tableau, and PowerBI to craft insightful dashboards and reports. 
• Infrastructure as Code Practices: Well-versed in infrastructure as code methodologies using tools such as Terraform for secure and efficient cloud infrastructure management. 
• Teamwork and Communication: Exceptional communication abilities, with a proven track record of effective collaboration within diverse, cross-functional teams. 

Professional Experience and Qualifications:

• Experience: At least 3+ years in analytics engineering or a similar role within a data-centric environment. Experience in a technology consultancy or professional services firm is preferred. 
• Education: Degree in Computer Science, Data Science, Information Systems, or a related field. 

Benefits

What We Offer in the UK: 

• Salary: Competitive salary and benefits package. 

• Pension: Up to 5% employer contribution, matching up to a 5% employee contribution, for a total of up to 10%. 
• Annual Leave: 4 weeks standard + 1 week additional annual leave over Christmas shut down period, plus public holidays. 
• Your Day - No Questions Asked: One additional day off per year, no explanation required! 
• Regular Lunches: Provided at team meet-ups and on workdays at Simple Machines' co-working space. 
• Health and Wellbeing Allowance: £1,250 allowance per year to be used for any food and non-alcoholic beverages during business hours, healthcare, gym memberships, sporting goods and accessories, and any wellness appointments. 
• Professional Development: £1,500 annual budget for training, courses, and conferences, with potential for additional funding. 
• Certifications: £2,500 annual budget for certifications and related courses. 
• Equipment Allowance: £1,500 for UK team members, plus Apple MacBook Pro laptops and necessary accessories. 
• Company Sick Leave: 10 days per annum, includes coverage for employee’s family. 
• Antenatal Support: Paid time off for antenatal appointments, including classes recommended by health professionals. 
• Terminal Illness Benefit: Three months' continuance of salary at full pay. 

Join Us: 

Simple Machines is a diverse and globally distributed team of individual talents. Everyone in the firm is among the best at what they do. That’s why they’re here. We have a collective obsession with the future and a passion to create real change through technology. If you’re someone who’s as passionate as we are about building a world-class technology company specialising in engineering for data, you’ll fit right in.