Python Engineer — Backend

2 weeks ago

Bengaluru, India Kalpas Innovations Full time

Contract duration : 6 months Role Overview :  We’re looking for a Python Engineer (2–4 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

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