Python Engineer Backend

5 days ago

Bengaluru, Karnataka, India ACI Global Business Services Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Job Title

Python Engineer Backend & Data Aggregations

Location

Bengaluru, India (Hybrid / Remote flexibility)

Role Overview

Were looking for a Python Engineer (4–7 years) who's strong in backend development and has hands-on experience implementing aggregation and data computation use cases — such as device-level rollups, metrics computation, time-based summaries, or multi-source joins.

You'll work closely with platform, data, and product teams to design efficient aggregation logic and APIs that serve real-time and historical analytics, and you'll help make Condense's data platform more intelligent and scalable.

Key Responsibilities

  • Design and implement data aggregation logic for device, customer, or time-window-based metrics using Python.
  • Build clean, maintainable backend services or microservices that perform aggregations and expose results through APIs or data sinks.
  • Work with internal teams to translate business or analytics needs into efficient aggregation pipelines.
  • Optimize data handling — caching, indexing, and computation efficiency for large-scale telemetry data.
  • Collaborate with DevOps and data teams to integrate with databases, message queues, or streaming systems.
  • Write high-quality, tested, and observable code — ensuring performance and reliability in production.
  • Contribute to design discussions, reviews, and documentation across backend and data infrastructure components.

Required Qualifications

  • 2–4 years of professional experience as a Python Developer / Backend Engineer.
  • Strong proficiency with Python (async programming, data structures, I/O, concurrency).
  • Experience with data aggregation, metrics computation, or analytics workflows (batch or incremental).
  • Sound understanding of REST APIs, microservice architecture, and database design (SQL/NoSQL).
  • Familiarity with cloud-native development and containerized deployment (Docker, Kubernetes).
  • Hands-on with data access and transformation using libraries like pandas, SQLAlchemy, or FastAPI/Flask for backend services.
  • Excellent debugging, profiling, and optimization skills.

Good to Have

  • Exposure to real-time data pipelines (Kafka, Kinesis, Pulsar, etc.) or streaming frameworks (Kafka Streams, ksqlDB, Faust).
  • Experience with time-series databases or analytics stores (ClickHouse, Timescale, Druid, etc.).
  • Understanding of event-driven or stateful aggregation patterns (tumbling/sliding windows, deduplication).
  • Familiarity with CI/CD, observability tools (Prometheus, Grafana), and monitoring best practices.
  • Experience working in IoT, mobility, or telemetry-heavy product environments.

What Success Looks Like

  • You deliver robust, scalable aggregation logic that enables downstream analytics and dashboards.
  • Code is clean, performant, and maintainable, following engineering best practices.
  • Aggregation jobs and APIs are well-monitored and observable, enabling smooth production operation.
  • You work effectively across teams — platform, DevOps, and product — to deliver data-backed insights faster.
  • You continuously learn and adopt best practices from the Python and data engineering ecosystem.

NOTE : Interested professionals can share their resume to

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