---
title: 'Software Development Engineer II – Data Engineer at Gather AI'
canonical: 'https://feeny.ai/job/software-development-engineer-ii-data-engineer-gather-ai-india-m69wab85ngtb'
type: 'job'
last_seen: '2026-10-15'
---

# Software Development Engineer II – Data Engineer at Gather AI

- **Company:** Gather AI
- **Location:** India
- **Work type:** remote
- **Posted:** 2026-09-30
- **Last confirmed live:** 2026-10-15
- **Apply:** https://job-boards.greenhouse.io/gatherai/jobs/5252951007

## Job description

## About Us

Are you ready to build the future of the supply chain? At Gather AI, we're not just creating software; we're pioneering a new era of warehouse intelligence. We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery.

If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.

## About the Team

You'll join the Full Stack group within Cloud Services, which is being built now. Today, production and analytical workloads share a single database, and each product defines its own metrics. This team exists to fix that by designing and building the warehouse, transformation layers, and semantic model from the ground up. You'll work closely with Full Stack, ML, Product, Security, and Customer Success.

## About the Role

Most data engineers early in their careers maintain one slice of a large, mature platform, or build pipelines against a model someone else designed years ago. This role is the opposite.

As an SDE II, Data Engineer, you'll be one of the first engineers building Gather AI's data foundation from scratch. The work includes:

- Moving analytics off our production PostgreSQL database
- Writing the layered dbt models every product will share
- Defining metrics once so they stay consistent everywhere
- Linking structured records back to the drone images and video they came from

You'll start by shipping well-scoped pipelines and models on our Drone product alongside senior engineers. From there, you'll grow toward owning a data domain end to end: its design, its quality, and its on-call.

This is a fully remote role on our India-based team. We work across multiple time zones, so clear written communication, initiative, and the ability to make progress independently matter.

## What You'll Do

- Build extraction pipelines. Move data from production PostgreSQL into the analytical warehouse (raw, refined, serving) using incremental loads that protect the production database.
- Build and extend the shared data model. Write and maintain dbt models, such as dimensions, reusable metric building blocks, and serving tables, following the architecture set by our Principal Data Engineer.
- Implement metrics. Add metrics to the semantic layer so a measure like "scan accuracy by site" is defined once and matches across every dashboard.
- Keep data trustworthy. Add tests, freshness checks, and alerts to the pipelines you build, and help run safe backfills when data needs correcting.
- Build in tenant isolation. Apply our access-control and tenant-separation patterns to every model and pipeline you ship.
- Maintain lineage. Keep metrics traceable to their source records and drone images, so any number can be checked against the original capture.
- Work at the ingestion boundary. Partner with the integration team to validate incoming WMS data against agreed contracts.
- Document your work. Keep models documented and registered in the data catalog.
- Ship safely. Deliver through CI/CD, use AI-assisted development, and join on-call for the pipelines you own.
- Grow with the platform. Start on the Drone product, then help onboard MHE Vision, 3D case counting products onto the same data foundation over the year.

## What You'll Need

- Experience: 2–5 years building and running production data pipelines, and a degree in Computer Science or equivalent practical experience.
- SQL: Strong SQL, including joins, window functions, and CTEs, plus a working understanding of dimensional modelling (facts, dimensions, grain). PostgreSQL experience preferred.
- Transformation: Hands-on experience building tested models in dbt, Snowflake Dynamic Tables, Databricks Lakeflow Declarative Pipelines, or equivalent.
- Python: Production pipeline code with tests and code review, beyond notebooks or one-off scripts.
- Orchestration: Experience running pipelines in Airflow, Dagster, Databricks Lakeflow Jobs, Snowflake Tasks, or equivalent, including handling failures, re-runs, and backfills.
- Data movement: Has loaded data from an operational database into a warehouse or lakehouse such as Snowflake or Databricks.
- Cloud: Production experience on Azure or another major cloud, including object storage, Git, CI/CD, and Docker/Kubernetes.
- Data quality mindset: Writes tests alongside code and cares whether data is correct, not just whether the job ran.
- Ownership and growth: Hands-on and curious. Digs into problems beyond their own code, brings ideas to the team, and takes review feedback well.
- Communication: Clear written and spoken English. Writes good PRs and documentation and raises blockers early in a distributed team.

## Nice to Have

- Change data capture (Debezium, Fivetran) or streaming (Kafka, Event Hubs)
- PySpark or Snowpark
- Terraform or other infrastructure as code
- Semantic layers (dbt Semantic Layer, Cube) or data catalogs (Purview, DataHub)
- Multi-tenant data platforms or row-level security
- Working with image, video, or sensor data alongside structured records
- Logistics, warehousing, or robotics domain experience

## About Gather AI

## Company Overview
- **One-liner**: Gather AI builds the Physical AI platform for logistics, using AI-powered vision on drones and material handling equipment to digitize warehouse operations in real time.
- **Entity Type**: Private – Series B ($74M total funding)
- **Headquarters**: Pittsburgh, United States
- **Founded**: 2017
- **Founders**: Sankalp Arora (CEO), Geetesh Dubey (Chief Systems Officer), Daniel Maturana (Chief ML Scientist)

## Core Business
- Primary industry: Logistics and warehouse management (Physical AI)
- Target customers: B2B, enterprise-scale logistics, manufacturing, retail, aerospace, automotive, and government – customers include GEODIS, NFI Industries, Barrett Distribution Centers, Axon, and dnata
- Mission: To give every facility in a network the same continuous picture of the floor, the intelligence to understand it, and the workflows to act on it – bringing the same intelligence to the physical world that exists in the digital one.

## Products & Services
- **Gather AI Prana Platform**: An end-to-end Physical AI platform with three layers:
  - **SEE**: AI-powered vision on forklift-mounted cameras (for moving items) and drones (for static inventory) that captures ten-plus structured data points per frame, achieving 99.9%+ inventory accuracy.
  - **THINK**: AI reasoning that investigates root cause across inventory, labor, and fulfillment, surfacing ranked, reasoned priorities before each shift.
  - **ACT**: Workflows that route decisions to the right person or system with pre-drafted tasks, closing the loop from capture to action.

## Market Standing
- **Valuation**: Not publicly disclosed (private company)
- **Key Metric**: 2.5x year-over-year bookings growth (250% growth); total funding of $74M (including a $40M Series B raised in 2026); average time to ROI is 6 months.
- **Notable Investors/Partners**: Backed by Tribeca Venture (noted on LinkedIn); deployed with GEODIS, NFI Industries, Barrett Distribution Centers, Axon, dnata, and the U.S. Department of Classified Antiquities.
- **Growth Signals**: Doubled operational footprint in 2026; named to Fast Company’s World’s Most Innovative Companies list for 2026; employee headcount grew ~68% year over year to 80+ employees; expanded into government sector; active job postings increased 333% YoY.

## Competitive Advantages
- **Closed-loop Physical AI**: Combines vision (SEE), reasoning (THINK), and action (ACT) in one platform – a unique integration that turns real-time visual data into prioritized tasks and automated workflows.
- **Deep domain expertise**: Founded by Carnegie Mellon robotics PhDs; CTO Andrew Hoffman was a founding engineer at Kiva Systems (now Amazon Robotics); team has decades of warehouse automation experience.
- **Network-wide consistency**: The platform enforces the same standard across every facility, enabling fixes from one building to become playbooks for the whole network.
- **99.9%+ accuracy** down to the case level, maintained continuously, not just during audits.

## Strategic Focus
- Scale platform across multi-facility enterprise networks and new verticals (government, aerospace, automotive).
- Continue investing in AI/ML autonomy and computer vision to expand the “THINK” layer’s root-cause analysis and predictive capabilities.
- Enhance network-wide outcomes by replicating operational playbooks across customer sites.

## Why Work Here
- **Culture**: Radical transparency, candor, accountability, speed, and a people-first approach. Decisions are made openly; everyone has a voice in shaping the company’s future.
- **Work model**: Fully remote or remote-flexible options available.
- **Benefits**: Competitive salary and equity, comprehensive medical/dental/vision, 401K, unlimited PTO, monthly wellness benefit, continuing education/tuition support, voluntary life insurance.
- **Engineering culture**: Opportunities to work on cutting-edge AI, ML, autonomy, computer vision, and robotics alongside former Amazon Robotics and CMU experts. Real customer impact at scale.

## Sources
1. [gather.ai](https://gather.ai)  
2. [gather.ai/company](https://gather.ai/company)  
3. [gather.ai/careers](https://gather.ai/careers)  
4. [gather.ai/about](https://www.gather.ai/about)  
5. [linkedin.com/company/gather-ai](https://www.linkedin.com/company/gather-ai)

## Other roles at Gather AI

- [ML Annotation QA Engineer](https://feeny.ai/job/ml-annotation-qa-engineer-gather-ai-open-to-fz96nnrq0f5c) — Open To, India
- [Staff Autonomy Engineer (MHE Vision)](https://feeny.ai/job/staff-autonomy-engineer-mhe-vision-gather-ai-open-to-xwrzam65zcy5) — Open To, United States / Pittsburgh, PA
- [Staff Autonomy Engineer (Drone)](https://feeny.ai/job/staff-autonomy-engineer-drone-gather-ai-open-to-9q1w90fjkesc) — Open To, United States / Pittsburgh, PA
- [Principal Data Engineer](https://feeny.ai/job/principal-data-engineer-gather-ai-india-gb7hgwbveemp) — India
- [Product Designer](https://feeny.ai/job/product-designer-gather-ai-open-to-6zhb7g3cbtkw) — Open To, United States / Pittsburgh, PA
- [Director of Machine Learning](https://feeny.ai/job/director-of-machine-learning-gather-ai-pittsburgh-rhtp64m9hkez) — Pittsburgh, PA / Open To, United States
- [Principal Robotics Systems Engineer](https://feeny.ai/job/principal-robotics-systems-engineer-gather-ai-pittsburgh-44pf3tm05xjx) — Pittsburgh, PA