• Build and own the platform backbone for governed reporting and trusted AI workflows. • Make strategic architecture calls and build, harden, or rebuild pipelines. • Partner closely with Analytics, Engineering, and vendors to turn fragmented source systems into trustworthy data products. • Ensure our data infrastructure integrates securely and reliably with core operational systems. • Handle requirements, source profiling, ingestion design, QA, documentation, and support for data integrations. • Manage dependencies, retries, alerts, incident response, and monitoring for pipeline reliability. • Help retire brittle reporting paths and manage Snowflake governance, data contracts, and data observability.

Role Description Fetch is looking for a Senior Data Engineer to join a cross-functional product team, working closely with machine learning engineers, backend engineers, and product managers to build robust data infrastructure that powers Fetch’s recommendation and audience targeting systems. In this role, you will take ownership of critical data infrastructure components, including: - Data transformation pipelines - Real-time event ingestion systems - Data contracts that ensure reliability across our platforms Your work will enable downstream services and applications to access high-quality, low-latency data at scale, processing terabytes of data daily. This position requires deep technical expertise in building scalable, reliable data systems, along with strong collaboration skills to translate cross-functional requirements into durable and well-designed solutions. Role Responsibilities - Design, build, and operate scalable data pipelines using batch and real-time processing technologies such as Apache Spark, Kafka, Flink, or managed cloud streaming services to process terabytes of data daily. - Build data infrastructure that ingests real-time events and stores them efficiently across databases, data warehouses, and data lakes within AWS. - Establish and enforce data contracts with backend engineering teams by implementing schema management, data quality checks, and monitoring to ensure pipeline reliability. - Make data accessible and consumable for operational services, analytics platforms, and data-intensive product features, balancing latency, freshness, and accuracy requirements. - Collaborate closely with backend engineers, machine learning engineers, and product partners to understand data access patterns, system constraints, and quality expectations. - Take ownership of significant portions of the data platform architecture, driving design decisions and technical prioritization. - Develop tools, frameworks, and recommended patterns that enable rapid development of data products and consistent pipeline deployments. - Mentor engineers on data engineering best practices and raise the overall quality bar across the organization. - Stay current with emerging technologies in data processing and infrastructure, evaluating their applicability and impact on Fetch systems. Recommendation Systems Team In this role, you will focus on building data infrastructure that powers Fetch’s recommendation systems. You will partner closely with machine learning engineers to design and implement the platforms and pipelines that enable personalized recommendations at scale. Key areas of focus include: - Building and maintaining feature store infrastructure to support efficient feature development, discovery, and reuse across recommendation models. - Designing and operating low-latency feature serving systems that power real-time recommendation APIs for both training and inference workloads. - Implementing monitoring and quality checks to ensure feature freshness, accuracy, and consistency. - Collaborating with ML engineers to understand feature access patterns, model requirements, and latency and throughput needs. Qualifications - 6+ years of professional experience in data engineering, building and operating production data systems at scale. - Proven experience designing, building, and maintaining scalable batch and real-time data pipelines capable of processing terabytes of data daily. - Hands-on experience with modern data processing frameworks such as Apache Spark, Kafka, Flink, Open Table Formats, and modern OLAP databases. - Strong foundation in data architecture principles, including data modeling, schema design, and tradeoffs between latency, reliability, and cost. - Proficiency in at least one modern programming language such as Go, Python, Java, or Rust, along with strong SQL skills. - Experience with Infrastructure as Code tools such as Terraform or CloudFormation in a production environment. - Familiarity with CI/CD processes and modern software development lifecycle practices, with an emphasis on shipping incrementally and improving systems over time. - Experience implementing data quality controls, including validation, monitoring, and anomaly detection. - Ability to take ownership of projects with guidance, driving designs from initial architecture through implementation and adoption. - Comfort presenting technical designs, participating in peer reviews, and constructively challenging decisions. - Strong collaboration skills with experience working closely with software engineers, machine learning engineers, data analysts, and product partners. - Undergraduate or graduate degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience. Compensation At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $149,523 - $206,578. Discover our benefits and how our employees live rewarded at https://fetch.com/careers .

• Build and maintain data pipelines that power analytics, ML workloads, and product-facing applications • Evolve our data platform alongside cloud platform engineers • Design and implement scalable data infrastructure • Develop data services and APIs that expose trusted data to product applications • Own data quality and observability • Partner with AI engineers, data scientists, analysts, and product teams to understand their data needs • Uphold strong data privacy, security, and compliance practices

Role Description As a Data Integration Engineer, you will contribute to connecting clients’ ERP and financial systems with Prophix to unlock the full potential of their data. Working closely with Professional Services and cross-functional teams, you will help design, build, and maintain integration solutions that automate the retrieval, transformation, and delivery of financial data. This is a hands-on technical role focused on: - API integrations - SQL-based data processing - Cloud-hosted environments - Financial data workflows You will gain practical experience working with: - ERP systems - Secure data pipelines - Scalable integration architecture You will primarily work on well-defined integration tasks, gradually building toward more complex problem-solving and solution design, while being supported by experienced team members through mentorship and collaboration. This is a permanent, full-time position, open to candidates based at a commutable distance from our Paddington office in London or fully remote within the UK. Qualifications - Degree in Computer Science, Engineering, Data, or related field (or equivalent practical experience) - Experience with SQL and relational databases - Familiarity with REST APIs and JSON - Programming knowledge in JavaScript, or a similar scripting language - Basic understanding of ETL concepts - Strong analytical thinking and attention to detail - Must have the right to work in the UK - Comfortable using AI tools responsibly to support tasks such as research, drafting, and data review - Able to learn new tools and adapt as technology and workflows evolve - Curious, open to new approaches, and motivated to continuously improve - Collaborative mindset when working across teams and with AI supported tooling Requirements - Exposure to ERP or accounting systems - Experience working with financial datasets (GL, trial balance, transactions, dimensions) - Familiarity with API authentication methods (OAuth 2.0, tokens) - Exposure to cloud platforms such as AWS or Azure - Understanding of integration design patterns or data flow architecture - Interest or experience in contributing to solution design discussions for client integrations Benefits - Hybrid set-up from our Paddington office or fully remote with flexible working hours - Private medical insurance through Vitality including mental health support and talking therapies - Income protection at 75% of earnings and death in service at 3x salary - NEST pension with 3% employer contribution - 25 days of annual leave, 10 sick/personal days on full pay, and 1 volunteer day - Total Wellness Benefit of £550/year - Professional development support and financial assistance for learning - Opportunities to participate in Environmental, Social, and Governance (ESG) initiatives - Quarterly Town Halls and Kickoffs that bring teams together to celebrate wins, share updates, and look ahead at what’s next