Analyst - CX (Operations and Data)

About the role

More of our customer experience now runs on systems rather than people: automated decisions, automated conversations, automated outreach, and rules that close a request without an agent. You will be the day-to-day owner of these systems, build the smaller ones yourself, and own the customer experience data underneath all of them.

Product and engineering build the core of each system. You own what happens around it: the rules and settings, the data it reads and writes, the testing before a change goes live, the monitoring after, and the weekly answer to "is it working, and what did it save?"

You will work across our ticketing, telephony, messaging and bot platforms, and our order, pharmacy, vet consultation and clinic data. You work in SQL, Python and scheduled jobs, with version control and code review. You report to the Senior Manager, Customer Experience.

What makes this role hard

- One customer, many identities. A pet parent can show up under two phone numbers, several orders, a pharmacy prescription, a vet consultation and a clinic visit, each in a different system with its own id. Every profile, call list and measurement you build depends on joining them correctly and saying how much of the data each join covers.
- Systems you do not control. Much of the stack is vendor platforms. Fields get renamed, new values appear without notice, and records are edited days after they are created. You work through their consoles and APIs, inside their limits, and you catch the change before a report goes wrong.
- Every rule cuts both ways. A threshold that stops bad claims can also slow down a genuine customer. An automated answer that handles more questions can also get some of them wrong. You measure both sides, every week, and bring the trade-off to your manager with numbers.
- Measuring what a system really did. Operations teams want every customer treated the same way. You set up holdout groups anyway, so impact is measured rather than assumed.
- Rules that apply to every call and message. Consent, do-not-disturb and telecom rules apply to automated outreach. Prescription and pet health data are sensitive. You build these rules into every campaign and every table, not as an afterthought.
- Spikes. Sale days and festival weeks double the load in hours. The systems and the data pipelines have to hold,



and you are the person who notices first when they do not.

What you'll do

Run the CX systems day to day

- Decision systems: keep the scoring and rules that decide customer requests working as agreed, apply approved changes, log every automatic decision, review wrong approvals and wrong declines every week, and flag drift before it costs money or trust.
- Conversation systems: maintain the content and logic of our automated conversations once changes are approved, and track quality, resolution and handover rates.
- Outreach systems: own the call flows, routing and campaigns on the CX side, and produce the daily work lists for customer-facing teams, measuring what each list produced.
- Customer profile: maintain one view of each customer across orders, conversations, calls, pharmacy, consultations and clinic visits, so every system and every person reads the same history.
- Hold every automated conversation and call to the same standard: full context on handover, an outcome on every session, a record for every call. Find and fix a broken flow before customers notice.

Change and measure them safely

- Test every rule, prompt or flow change on test records, test numbers or a small slice of customers before it goes live, and read back what was stored.
- Report each system every week: what it decided, how often it was right, what it saved, and what it cost when it was wrong, against the impact assumed when it was approved.
- Be first on call when a system misbehaves: pause it, tell the owner, find the cause, and write down the fix, with a named second on call and a written runbook for each system.

Build the smaller systems yourself

- Build tools and automations in Python, spreadsheet scripting, internal-tool builders or with AI coding assistants: quality audits on chats and calls, ticket automation rules, alerts, and small integrations through APIs and webhooks.
- Take over and maintain integrations and prototypes once they are live.




- Make sure automated flows write the right fields into each record: define the payload, test it, check what was stored and alert on failures.
- Keep code in our repositories, reviewed before release and documented. Back up before you overwrite, and read back after you write.
- Review the output of AI coding assistants as carefully as you would a colleague's.

Own the CX data

- Own the customer experience tables from source to report: grain, keys, coverage dates, and the pipelines that fill them, with backfills, run logs and look-back reconciliation for records edited later.
- Define metrics in writing (population, date anchor, rule, denominator) and build the CX dashboards on them. When two dashboards disagree, find out why and take the fix to your manager.
- Own the mappings from platform fields, channels, queues, statuses, campaigns, dispositions and agents to analytics columns, with a check after every change and a visible bucket for unknown values.
- Reconcile tables to each source per day and per team, check freshness, catch schema changes, duplicates and blank rates, and handle timezones and late records explicitly.
- Work with least-privilege access, keep secrets out of code, and collect only the personal data a table needs.

Turn requests into shipped work

- Write the requirement notes for new automations and changes: problem, rules, data, test plan and how success is measured. Your manager signs them off before they go to Product.
- Take your own projects from first request to rollout: a pilot, then coordination with engineers and vendors.
- Keep the weekly review numbers dependable, and answer ad hoc questions with findings and a recommendation.

What we're looking for

- 3 to 6 years in analytics, analytics engineering or product operations, including at least a year owning tables, pipelines or a live system other people depend on.
- Robust SQL: joins, CTEs and window functions, with queries you can explain and tune.
- Python for pipelines, scheduled jobs and automation, and comfort with version control and code review.
- You have run or changed a live automated system (a bot, a rule engine, an outbound calling campaign, a scoring model) and measured what it did.
- You can turn a vague request into a requirement note an engineer can build from, and explain results to non-technical teams.

📌 Analyst, Customer experience (Bengaluru)
🏢 SuperTails
📍 Bengaluru