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Senior API Data Analyst

impact · Cape Town · Cape Town, Western Cape, South Africa
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<h2><strong>About impact.com</strong></h2> <p><a href="http://impact.com/">impact.com</a> is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates,<a href="http://impact.com/"> impact.com</a> empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products—<strong>Performance</strong> (affiliate), <strong>Creator</strong> (influencer), and <strong>Advocate</strong> (customer referral)—unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust,<a href="http://impact.com/"> impact.com</a> helps brands show up where it matters most. Today, over 5,000 global brands, including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics, rely on<a href="http://impact.com/"> impact.com</a> to power more than 225,000 partnerships that deliver measurable business results.</p> <h2><strong>Your Role at</strong><a href="http://impact.com"><strong> </strong><strong>impact.com</strong></a><strong>:</strong></h2> <p>The API Analyst keeps a company-wide picture of how our APIs are used, what they cost, and where integrations go wrong, and turns that picture into a weekly operating loop. You work where the public API meets the systems behind it. The teams that own each API own its behaviour, its caching, and how large a customer's limit should be. Gateway and platform engineers own how those limits are enforced. This role supplies the evidence, the automation, and the weekly pressure those decisions need. You do not take over another team's product to make the change. Day to day you live in request logs, latency and row-volume signals, rate-limit behaviour, and partner usage patterns. You automate the checks that turn a one-off investigation into a continuous view of API health. Each week you work that view: catch misuse and bad integration patterns, name APIs that should be retired or capped, triage alerts, and hand the owning team a record they can act on. When a problem sits in one integration, you help shape a proportionate response so the platform stays stable and everyone else's access stays usable. You also help say what good looks like for customers. The same usage record should drive the story we tell integrators: which patterns we support, which ones we will not, and what we expect under contract. You are technical enough to build those checks yourself and to read the relevant code with the team that owns a change. You are senior enough to take a hard finding to the front and keep the response the size of the problem.</p> <h2><strong>What You'll Do:</strong></h2> <h3> 1. Run API usage as an operating loop</h3> <ul> <li>Build a continuous picture of how our APIs are actually used: who is calling what, at what volume, with which date ranges, paging patterns, concurrency, and how widely a single integrator's traffic is spread.</li> <li>Detect and explain fan-out risk: traffic that looks fine for one account but becomes a platform incident when a partner spreads load across many accounts at once.</li> <li>Each week, work the API usage record. Identify misuse, bad integrations, spikes, and APIs that should be retired or capped. Triage the alerts. Keep a living history so the next incident starts from evidence.</li> <li>Separate expensive work from cheap work: understand when a long-running call was waiting in a queue versus actually heavy, and when a wide date range costs more or less than many narrow ones.</li> <li>Hand the owning teams the metrics they use to choose caching, rate-limit sizes, date-range caps, and concurrency. Stay with them until the evidence is understood. The decision stays with the team that owns the API.</li> </ul> <h3>2. Turn observability into evidence for guardrails</h3> <ul> <li>Automate analysis across log search, data warehouses, and reporting tools: recurring checks, red flags, and briefings that surface bad patterns early, including with AI-assisted triage where it earns its keep. Building those checks is the job.</li> <li>Propose concrete limits grounded in real usage plus room to grow: short bursts, sustained rates, and a ceiling across an integrator's full footprint. Pressure-test the proposal with the team that owns the API and with the gateway team.</li> <li>Partner with gateway and platform engineers on how rate limits, access tokens, and HTTP 429 responses enforce the limits those teams have set.</li> <li>Recommend patterns such as date-range caps, concurrency limits, synchronous versus asynchronous versus streaming delivery, and limited-scope credentials. Follow the evidence through with the owning team. They make the product change.</li> </ul> <h3>3. Raise the bar on integration patterns and the customer story</h3> <ul> <li>Study how large partners and peers integrate, including synchronous, asynchronous, streaming, and bulk export, and how they cap concurrency. Bring clear recommendations back into our API offering.</li> <li>Work with partnership and product colleagues on strategic and enterprise partners so proposals for rates, spare capacity, and migration reflect platform cost and risk as well as the commercial goal. Partnership owns the commercial terms. You own the cost and misuse evidence those terms have to survive.</li> <li>Help define

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