Role : Staff Engineer, Data Platform

Team: Data Engineering - Level: Staff (Individual Contributor) - Experience: 8+ years - Full-time

Own the data platform that turns every customer and field interaction into a decision SolarSquare can act on.

About SolarSquare :

At SolarSquare we are building the Home-Energy brand of future India. We help homes switch to rooftop solar and move away from traditional coal electricity. We are a full-stack D2C residential solar brand - designing, installing, maintaining (after-sales), and financing solar systems for home-owners across India.

About the role :

As a Staff Engineer on Data Platform, you set the technical direction for how we move, model, and serve data across the entire customer lifecycle - from real-time operational streams off thousands of field devices to the analytical layer our leaders and AI systems depend on. You operate at the scope of the platform: ambiguous problems land on your desk, and you turn them into systems the whole org builds on.

What you'll own :

- Design and scale the data platform end to end: streaming ingestion, batch pipelines, the analytical warehouse, and a governed self-serve metrics layer.

- Build real-time operational data streams that power field operations and customer-facing experiences with low latency and high reliability.

- Own data quality, lineage, and governance - including PII handling - so teams trust the data and never dump it mindlessly.

- Define a golden metrics layer and the standards, contracts, and tooling that make analytics self-serve across the org.

- Set the bar on craft: review designs, clear data tech debt every sprint, and mentor engineers across pods.

The Tech you'll work with :

You'll work across event streaming (Kafka), PostgreSQL as the system of record, a columnar analytical warehouse for OLAP, Python-based pipelines, and Metabase for self-serve BI - with more workloads moving to real-time and columnar storage as we scale.

What we're looking for :

- 8+ years building large-scale data systems in production, with deep ownership of at least one major data platform.

- Strong command of distributed data processing and streaming architectures, plus modern columnar / analytical warehouses.

- Expert SQL and data modeling; fluency in data quality, lineage, and governance.

- Proven ability to turn ambiguous business questions into durable data models and reusable platform abstractions.

- Experience setting technical direction and growing the engineers around you.

- Customer-obsessed and impact-led: you start from the customer's pain and judge yourself by the metric your work moves, not the tickets you close.

- High agency: you don't wait to be told - you spot problems, pick them up, and own the outcome through to production.

- Craft over shortcuts: you fix root causes rather than symptoms, clear tech debt as you go, and don't ship bugs.

- Bias for speed and simplicity: you build once for reuse, automate the mundane, and let AI draft the first pass so your judgment goes where it matters.

- Data-driven: you reach for evidence over assumptions and let results guide the next decision.

Bonus points :

- Experience with lakehouse architectures, real-time analytics, or geospatial / IoT-scale data.

- Exposure to semantic layers and self-serve analytics platforms.

- Built data platforms that feed ML or AI systems.

Why you'll love building here :

- Direct ownership of high-impact initiatives with visible customer and business outcomes.

- An AI-native engineering culture with first-class tooling and internal agents.

- A high-agency, low-bureaucracy environment where you debate what's right and ship.

- A meritocracy where growth and recognition track impact, not tenure.

- Competitive compensation.

- A front-row seat to putting clean energy on millions of Indian rooftops.