This range is provided by Cognify Search. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Overview

Cognify are hiring for a fast-growing B2B SaaS company that provides large-scale data solutions to businesses and organisations worldwide. The platform serves millions of users and handles complex, high-volume datasets across multiple regions. The company’s mission is to deliver fast, reliable, and high-quality data to customers through APIs, search, and other data delivery channels. To achieve this, they are seeking a talented engineer to optimise the performance, structure, and accessibility of their data platform.

Search & Data Platform Engineer

Cognify are looking for a Search & Data Platform Engineer to focus on performance, organisation, and optimisation of data across the company’s customer-facing platform. This role sits at the intersection of data engineering and platform engineering. The main focus is on how data is structured, indexed, cached, and delivered through APIs, search, and bulk/delta/streaming products, rather than building ingestion pipelines. The successful candidate will collaborate with platform and product teams to ensure fast, scalable, and developer-friendly data delivery, while improving the search and query experience across products.

Key responsibilities

• Optimise data delivery by designing and maintaining performant access layers for APIs, search, bulk/delta deliveries, and streaming services.
• Improve search systems and indexing strategies to ensure fast, accurate, and relevant results at scale.
• Structure and model datasets to balance usability, consistency, and performance.
• Implement multi-layered caching solutions (query caching, materialised views, edge/CDN caching, object storage pre-computation) to achieve consistently low-latency responses.
• Tune queries and indexes for high-throughput, low-latency data retrieval.
• Collaborate with architects and engineers to ensure consistency and efficiency across the data delivery stack.
• Design scalable and resilient solutions capable of handling large volumes and usage spikes without compromising reliability.
• Implement observability for search, caching, and queries to proactively identify and resolve bottlenecks.
• Ensure APIs and search systems are intuitive for developers, with clear contracts and predictable performance.

Technical expertise required

• Experience with search technologies such as Elasticsearch, OpenSearch, Solr, or similar.
• Proficiency in query optimisation and schema design for relational and/or NoSQL databases.
• Experience tuning search queries, database queries, and cache layers for large-scale platforms.
• Familiarity with designing or supporting APIs for external consumers.
• Experience with cloud environments, preferably AWS, including services such as RDS, DynamoDB, S3, CloudFront, and Redis/ElastiCache.
• Understanding of data delivery patterns (batch, bulk export, delta updates, streaming) and optimising their access paths.
• Strong programming skills in at least one modern language (Python, Go, Ruby, etc.), particularly for data tooling and optimisation.

Collaboration & problem solving

• Work closely with architects, backend engineers, and product managers.
• Strong problem-solving skills with a pragmatic approach to balancing performance, complexity, and maintainability.
• Clear communicator, able to explain technical concepts to varied stakeholders.
• Flexible hybrid working culture, with opportunities for remote and in-person collaboration.
• 28 days annual leave plus bank holidays, with an extra day per year of service.
• Flexibility to work abroad for up to 4 weeks per year.
• Regular company socials.
• Discretionary leave for milestone life events (e.g., birthdays, weddings).
• Private healthcare, life assurance, and an annual wellbeing budget.
• Personal development budget and learning days.
• Cycle to work scheme.
• £500 home office set-up budget.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology, Engineering, and Analyst

Industries

Data Infrastructure and Analytics

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