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Reelo

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Senior Backend Engineer

Full-timeSeniorPosted Oct 22, 2026

Job description

About Reelo Reelo is a customer retention platform for restaurant and retail brands. It covers loyalty, feedback, customer segments and WhatsApp, SMS and email campaigns.

About the Role

Every bill, feedback and loyalty transaction from every outlet on our platform flows through our Express.js APIs. It then moves through AWS (Lambda, Kinesis, SQS, S3) into MongoDB and Click. House. As a Senior Backend Engineer, you will own these APIs, event pipelines and data stores. You will decide how the system grows, what it costs each month, how fast each dashboard loads and what breaks at 10x volume.

We also work AI-first. You will use Claude Code daily with the right skills, plugins and MCP servers, and you will review every line it writes. What You’ll Do Build and own APIs: Design, ship and version Express.js REST APIs for dashboards, POS integrations, campaigns and partner webhooks, with validation, auth, rate limits and clear contracts.

Run event pipelines: Keep Kinesis Data Streams, Lambda consumers and SQS workers correct under load, with idempotent writes, retries, dead-letter queues, backpressure and replay. Choose the right store for each workload: Keep transactional data in MongoDB and move heavy analytics to Click. House (materialized views, Aggregating.

Merge. Tree, the right ORDER BY keys). Use S3 for archives and bulk exports. Own cost: Know what each service, query and job costs per month. Find the top spenders in AWS and Click. House Cloud, cut them and show the savings in numbers. Own performance: Profile slow endpoints and queries using MongoDB explain plans and Click.

House query_log. Fix indexes and access patterns, and hold p95 latency targets. Plan for scale: Design for 10x data volume with sharding, partitioning, TTL and retention policies, hot/warm/cold storage tiers and autoscaling for ECS workers. Protect data correctness: Find and fix race conditions, double-counting and drift between MongoDB and Click.

House, especially in money-like data such as loyalty points and credit wallets. Raise the bar: Write short design docs, review pull requests carefully, mentor engineers and help shape how the team uses AI coding tools. Our Stack Core (you should be strong in these): API: Node.js, Express.js, Joi/AJV, JWT/Passport, Swagger Transactional data: MongoDB with Mongoose (aggregations, indexes, transactions) Analytics: Click.

House Cloud with the @clickhouse/client Node.js client (Merge. Tree family, materialized views, dictionaries) Streaming: AWS Kinesis Data Streams, Lambda consumers Background jobs: AWS SQS, ECS Fargate workers, Event. Bridge Scheduler, Redis + Bull Storage: AWS S3 (imports, exports, archives, presigned URLs) Quality: Jest, Supertest, ESLint, Prettier, Husky Learn on the job: Deploy and infra: Serverless Framework, Docker, ECS autoscaling, SSM Observability: Datadog APM (dd-trace), Cloud.

Watch, Winston What You Bring 5+ years of backend engineering, including 3+ years running Node.js and Express.js services in production for real customers. Deep MongoDB expertise. You can read an explain plan, design compound indexes in the right field order, write aggregation pipelines that avoid full collection scans, and know when a document is too big or a collection needs sharding.

Hands-on Click. House experience, or another columnar store you’ve run in production (Big. Query, Redshift, Druid, Snowflake). You understand sort keys, partitions, materialized views, and why FINAL and JOINs get expensive. Experience with AWS event-driven systems (Lambda, Kinesis Data Streams, SQS, S3). You know shard limits, batch sizes, visibility timeouts, partial batch failures, cold starts and dead-letter queues.

Cost thinking. You’ve cut a real cloud bill and can explain how, whether through right-sizing, batching, caching, retention, storage tiering or moving work off the wrong database. Performance and scale experience. You’ve taken an endpoint or job from seconds to milliseconds, or from 100K to 100M rows, and measured it before and after.

Strong API design skills: resource modelling, pagination, idempotency keys, versioning, consistent errors, and security basics (OWASP, input validation, NoSQL injection, rate limiting). Correctness under concurrency. You recognise lost updates, double-processing and race conditions, and fix them with atomic operators, transactions, idempotency or locks.

Clear communication. You can write a one-page design doc covering trade-offs and costs, and explain a production incident without blame. AI-Assisted Development We use Claude Code as a core engineering tool, not just autocomplete. We want someone who has already used it on real work and can show us how. You should be fluent with most of the toolkit on day one and able to extend it.

Our expectations: You own every line. You read and understand each diff the agent writes before it goes to review. Evidence before “done”. Tests pass, queries are benchmarked on real data volumes and edge cases are checked. You don’t take the agent’s summary on trust. Safe by default. Agents get read-only access to production data.

No secrets go in prompts, and destructive commands need a human. Context engineering. You keep CLAUDE.md, skills and plans current so the agent improves for the whole team. Token cost awareness. You choose the right model and effort for the task, just as you would right-size an EC2 instance.

Nice to Have

Change data capture from MongoDB to Click. House (PeerDB, Click. Pipes, Debezium) or Kinesis Data Firehose into S3 Data lifecycle work: TTLs, archiving to S3 or Parquet, and hot/warm/cold tiering with defined retention rules Building AI features on the Claude API or AWS Bedrock (tool use, prompt caching, structured output, vector retrieval) Infrastructure as code (Serverless Framework, CDK or Cloud.

Formation) and ECS autoscaling policies Messaging at volume: WhatsApp Business API, SMS gateways, email delivery and webhooks Payments or billing systems (Razorpay, Chargebee), or any ledger-style data where every unit must reconcile Experience in B2B SaaS, retail tech, restaurant tech or loyalty products Open-source contributions, or Claude Code skills and plugins you’ve written and shared

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