Software Development Engineer 2

2 weeks ago


Gurgaon, Haryana, India Boon Full time ₹ 15,00,000 - ₹ 28,00,000 per year

About Boon

Boon (by Swajal) builds IoT-enabled drinking-water systems used by leading hotels, offices, and communities. Our "UltraOsmosis + WaterAI" stack monitors water quality in real time, powers predictive maintenance, and enables plastic-free hydration at scale.

The Role

We're hiring an
SDE II (Backend)
to own and scale our IoT backend: secure device connectivity, telemetry ingestion, time-series data pipelines, APIs for apps/dashboards, and reliability at thousands of edge devices. You'll design services, write production code, lead small projects end-to-end, and mentor junior engineers.

What you'll do

  • Own services end-to-end:
    design docs, implementation, tests, IaC, and production rollout.
  • IoT data plane:
    MQTT topics & policies, device registry/shadows, OTA update flows, secure provisioning.
  • Data pipelines:
    high-volume ingestion → storage → query (time-series + metadata).
  • APIs & integrations:
    build/maintain internal & public APIs for apps, dashboards, partner integrations.
  • Reliability & scale:
    SLOs, error budgets, autoscaling, back-pressure, dead-lettering, retries.
  • Security & compliance:
    least-privilege IAM, secrets, audit logging, encryption in transit/at rest.
  • Observability:
    logs/metrics/traces, runbooks, dashboards, on-call participation.
  • Quality:
    code reviews, unit/contract/integration tests, CI/CD, performance profiling.
  • Tech leadership:
    break down work, align stakeholders, mentor SDE-I/interns.

Our stack (experience with analogous tech is fine)

  • AWS IoT Core
    , Device Registry/Shadow,
    API Gateway
    ,
    Lambda
    ,
    ECS/Fargate
    or
    EKS
    ,
    S3
    ,
    DynamoDB
    ,
    Timestream
    (or TimescaleDB/Influx),
    Kinesis/SQS/SNS
    ,
    CloudWatch
    ,
    Cognito
    ,
    IAM
    .
  • Protocols:
    MQTT, HTTP; familiarity with Modbus/LoRaWAN is a plus.
  • Languages:
    or Python/Go; SQL/no-SQL data modeling.
  • Infra:
    Terraform/CDK, GitHub Actions, containerization.
  • Obs:
    OpenTelemetry, Grafana/CloudWatch.

Must-have qualifications

  • 3–6 years' backend experience, with
    at least 2 years on AWS
    in production.
  • Built and operated
    event-driven
    or
    time-series
    systems handling high-volume telemetry.
  • Strong in
    API design
    ,
    data modeling
    , and
    distributed systems fundamentals
    (idempotency, deduplication, retries, ordering, consistency).
  • Hands-on with
    AWS IoT Core + MQTT
    (policies, certificates, shadows) OR equivalent IoT platform.
  • Proficient with
    DynamoDB/Timestream (or similar)
    , stream processing (Kinesis/SQS/Kafka), and
    IaC
    .
  • Solid testing discipline and CI/CD; can debug complex issues across services.
  • Clear communication, product sensibility, and the ability to lead 1–2 engineers on a workstream.

Nice-to-have

  • OTA update pipelines, device provisioning at factory, PKI/cert management.
  • Edge computing patterns, offline sync, back-pressure at gateways.
  • Experience with Grafana/Loki/Tempo, Prometheus, or CloudWatch X-Ray.
  • Security reviews/threat modeling for IoT fleets.
  • Exposure to

    (for internal tools) is a bonus.

Example projects you might own in your first 90 days

  • Telemetry pipeline v2:
    Kinesis → Lambda → Timestream with partition strategy, TTLs, and cost guards.
  • Device shadow service:
    unify configs/alerts across WaterCube/Refill SKUs; safe rollout guards.
  • Fleet OTA:
    signed firmware/artifact hosting, staged rollouts, automatic rollback on failure signals.
  • Partner API:
    rate-limited, token-scoped endpoints for enterprise customers; audit trails & webhooks.

How we measure success

  • Uptime & latency SLOs met; clear runbooks and dashboards.
  • Cost per device and data retention within targets.
  • Safe releases with automated rollbacks; low MTTR on incidents.
  • Developer experience: faster CI, better tests, fewer regressions.
  • Mentorship: peers learn from your reviews and docs.

Why Boon

  • Mission with tangible impact: clean water, less plastic, happier guests.
  • Ownership of meaningful systems at real-world scale.
  • Pragmatic engineering culture: clarity, outcomes, and craftsmanship.


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