Solarsquare energy pvt ltd
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PostgreSQL
PythonSOLARSQUARE · ENGINEERING
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.
In a few short years we have scaled to become the leading residential solar brand in India. We are obsessed with quality, customer service, and innovating to make it simple for homes to switch to solar. We are looking for leaders to join us in this mission.
Get to know us
- SolarSquare - company website
- Featured by TIME as one of the World’s Top GreenTech Companies of 2025
- SolarSquare raises $53M Series C led by B Capital (Moneycontrol)
- India’s rooftop solar market and SolarSquare’s growth (TechCrunch)
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. We’re stack-agnostic for the right person; fundamentals matter more than any one tool.
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.
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