Pure Dating - 173tech

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Flexible data engineering support for a growing team

Objective

Provide flexible, on-demand data engineering support while Pure expanded their internal team.

Obstacle

A growing backlog, technical debt, and inefficient queries were slowing progress .

Outcome

Data sources were centralised, queries optimised, and performance improved.

Background

Sometimes, scaling quickly means calling in reinforcements. That was the case for Pure, a fast-growing dating app, as they sought to strengthen their data engineering capabilities.

While the recruitment process for permanent hires was underway, the team faced a mounting backlog of work and an increasingly complex data environment. They needed experienced engineers who could jump in immediately; flexible, capable, and fast. That’s where 173tech came in.

Challenges

Flexibility: Pure needed interim support to bridge the resource gap while hiring permanent staff. Our flexible model provided hands-on engineering expertise on-demand, delivering results without the overhead or delay of a full-time team.

Technical Debt: This project serves as a clear example of how technical debt can gradually build up over time. As we delved into Pure’s data infrastructure, we discovered that several existing models had significant overlap and were not optimised for performance. This redundancy not only increased complexity but also led to inefficiencies, such as longer query run times and unnecessary rework for the analytics team.

Solution

Efficiency: The lack of streamlined, well-structured models meant that analysts had to spend extra time cleaning and transforming data before deriving insights, slowing down decision-making processes. By addressing these inefficiencies, we helped Pure enhance the performance and maintainability of their data models, ultimately improving overall system efficiency.

Add More Data: To enhance Pure’s data infrastructure and provide a more comprehensive view of their business performance, we integrated several new data sources into their ecosystem. These included CardPay, which streamlined financial transaction data, and Huawei Revenue, enabling better tracking of revenue from Huawei’s ecosystem. On the marketing side, we connected Twitter Ads, Snapchat Ads, and VKontakte Ads, allowing Pure to consolidate their advertising performance data across multiple platforms.

Impact

Flexibility: From backlog management to implementing new best practices, our engagement was tailored to Pure’s changing needs. This adaptive approach kept projects moving seamlessly while the company finalised internal hires.

One Source Of Truth: By centralising financial and advertising data, we improved reporting accuracy, enhanced marketing attribution, and enabled deeper insights into user engagement. The result was cleaner data, faster analysis, and better decisions across teams.

Fractional Support: Pure’s collaboration with 173tech demonstrates how agile, short-term data engineering support can deliver long-term value. By tackling technical debt and enabling a stronger data foundation, Pure was able to continue scaling confidently, supported by optimised systems and efficient workflows.