Principal Data Engineer

Gather AI

Principal Data Engineer architecting a data foundation for AI-driven products at Gather AI. Designing a multi-layer data warehouse and ensuring data quality and governance.

Posted 7/14/2026full-timeRemote • 🇮🇳 IndiaLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive expertise in architecting greenfield data warehouses and implementing multi-layer transformation architectures, ensuring data quality, security, and governance across production environments. Proficient in cloud data engineering, pipeline orchestration, and real-time data ingestion to support analytics and AI-driven products.

Highest-signal resume keywords

Data Warehouse ArchitectureExpert SQL and dbtCloud Data Engineering (Azure Preferred)Data Quality and GovernancePipeline Orchestration and Workflow Automation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Transformation and ModelingMulti-Layer Transformation ArchitecturesReal-Time and Streaming IngestionLarge-Scale Batch Data ProcessingSemantic and Metrics-Layer DesignOLTP to OLAP TransitionInfrastructure as CodeCI/CDData Quality and ObservabilityMulti-Tenancy Design

Tools & Technologies

AzureAWSGCPDbtELTData Catalog (Purview, DataHub)Workflow Automation Tools

Industry Keywords

Data EngineeringAnalyticsAI-Driven ProductsData GovernanceTenant IsolationAccess ControlData Lineage

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformSQL

About the role

Key responsibilities & impact

Architect a greenfield, multi-layer data warehouse (raw, refined, serving) that separates analytical workloads from production OLTP traffic.
Deliver a governed, self-service data-access layer for internal consumers first (Product, CSM, Deployment/Operations, and Leadership) as Phase 1, ahead of customer-facing conversational analytics.
Build a semantic and metrics layer so every metric, such as "scan accuracy by site," is defined once in code and stays identical across every dashboard and product, making self-service safe from metric drift.
Own the quality bar: 99%+ availability SLA with freshness guarantees, 100% traceability, zero cross-tenant leakage, 99.5%+ pipeline success, and no data loss.
Design tenant isolation, per-tenant cost attribution, and schema and row-level RBAC to scale toward hundreds of tenants (300+ target), not today's fleet size.
Own data-ingestion correctness at the boundary with the integration/backend team, covering data contracts, schema validation, and pipeline quality, so WMS data lands in the right place, shape, and time across WMS versions.
Stand up a data catalog and lineage layer (Purview as the Azure-native fit, DataHub as the open-source alternative) so every consumer can find data, see ownership, and trace lineage when a metric looks wrong.
Prove the foundation end to end on Gather's drone product, then generalize it so each new product extends the model instead of rebuilding it
Act as the connective tissue between product and ML (3DCC, damage detection). Link structured records to unstructured drone imagery and video with full traceability, and stand up the data-infra readiness for feature stores and annotation pipelines on one trusted foundation.

Requirements

What you’ll need

10+ years in data engineering, with 3+ years architecting data platforms for data products, analytics, or AI-driven products.
Proven experience building a greenfield data warehouse and leading an OLTP to OLAP transition, not just maintaining an existing one.
Deep expertise designing multi-layer transformation architectures and reusable frameworks that scale across multiple product areas.
Expert SQL and dbt, hands-on ELT and orchestration, and large-scale or streaming data experience.
Production experience on a major cloud (Azure preferred, AWS or GCP acceptable), plus infrastructure as code and CI/CD.
Track record with data quality, security, governance, and multi-tenancy in production environments.
Data transformation and modeling that turns raw multi-source data into refined, serving-ready datasets (raw to refined to serving).
Pipeline orchestration and workflow automation for scheduling, dependency management, and reliable execution across data flows.
Large-scale and distributed processing of high-volume batch data.
Real-time and streaming ingestion that captures and processes event data as it arrives.
Semantic and metrics-layer design that defines business metrics once and serves them consistently to every consumer.
Serving-layer optimization for fast, low-latency consumption through wide and flattened tables and pre-computed metrics.
Cloud data engineering and infrastructure automation that provisions, deploys, and operates the platform reproducibly (cloud-native, infrastructure as code, CI/CD).
Data quality, observability, and lineage that ensure trust, freshness, and end-to-end traceability.
Security, governance, and multi-tenancy including tenant isolation, access control, and resiliency.
Multimodal data integration that links structured records to unstructured image and video (drone captures) with traceability.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Gather AI Website LinkedIn All Job Openings 11 - 50 employees Founded 2018 🤖 Artificial Intelligence 🚗 Transport 🔧 Hardware 💰 $10M Series A on 2022-10 Artificial Intelligence
Transport
Hardware Gather AI is a company specializing in automated inventory monitoring solutions using AI-powered drones. They enhance supply chain visibility and warehouse efficiency by offering real-time inventory intelligence, significantly reducing human error and inventory shrinkage. Their autonomous drones facilitate automated data collection and analysis, enabling fast and effective decision-making with increased productivity and accuracy. Gather AI serves industries such as 3PL, manufacturing, retail, and food and beverage, providing a modern approach to warehouse management through innovative technology. Principal Data Engineer 🔥 2 hours ago 🇮🇳 India – Remote ⏰ Full Time 🔴 Lead 🚰 Data Engineer AWS Azure Cloud Google Cloud Platform SQL Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Architect a greenfield, multi-layer data warehouse (raw, refined, serving) that separates analytical workloads from production OLTP traffic.
Deliver a governed, self-service data-access layer for internal consumers first (Product, CSM, Deployment/Operations, and Leadership) as Phase 1, ahead of customer-facing conversational analytics.
Build a semantic and metrics layer so every metric, such as "scan accuracy by site," is defined once in code and stays identical across every dashboard and product, making self-service safe from metric drift.
Own the quality bar: 99%+ availability SLA with freshness guarantees, 100% traceability, zero cross-tenant leakage, 99.5%+ pipeline success, and no data loss.
Design tenant isolation, per-tenant cost attribution, and schema and row-level RBAC to scale toward hundreds of tenants (300+ target), not today's fleet size.
Own data-ingestion correctness at the boundary with the integration/backend team, covering data contracts, schema validation, and pipeline quality, so WMS data lands in the right place, shape, and time across WMS versions.
Stand up a data catalog and lineage layer (Purview as the Azure-native fit, DataHub as the open-source alternative) so every consumer can find data, see ownership, and trace lineage when a metric looks wrong.
Prove the foundation end to end on Gather's drone product, then generalize it so each new product extends the model instead of rebuilding it
Act as the connective tissue between product and ML (3DCC, damage detection). Link structured records to unstructured drone imagery and video with full traceability, and stand up the data-infra readiness for feature stores and annotation pipelines on one trusted foundation. 🎯 Requirements
10+ years in data engineering, with 3+ years architecting data platforms for data products, analytics, or AI-driven products.
Proven experience building a greenfield data warehouse and leading an OLTP to OLAP transition, not just maintaining an existing one.
Deep expertise designing multi-layer transformation architectures and reusable frameworks that scale across multiple product areas.
Expert SQL and dbt, hands-on ELT and orchestration, and large-scale or streaming data experience.
Production experience on a major cloud (Azure preferred, AWS or GCP acceptable), plus infrastructure as code and CI/CD.
Track record with data quality, security, governance, and multi-tenancy in production environments.
Data transformation and modeling that turns raw multi-source data into refined, serving-ready datasets (raw to refined to serving).
Pipeline orchestration and workflow automation for scheduling, dependency management, and reliable execution across data flows.
Large-scale and distributed processing of high-volume batch data.
Real-time and streaming ingestion that captures and processes event data as it arrives.
Semantic and metrics-layer design that defines business metrics once and serves them consistently to every consumer.
Serving-layer optimization for fast, low-latency consumption through wide and flattened tables and pre-computed metrics.
Cloud data engineering and infrastructure automation that provisions, deploys, and operates the platform reproducibly (cloud-native, infrastructure as code, CI/CD).
Data quality, observability, and lineage that ensure trust, freshness, and end-to-end traceability.
Security, governance, and multi-tenancy including tenant isolation, access control, and resiliency.
Multimodal data integration that links structured records to unstructured image and video (drone captures) with traceability. Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs Staff Fullstack Engineer – Data Products 🕒 Yesterday GitLab 1001 - 5000 🤖 Artificial Intelligence 🏢 Enterprise ☁️ SaaS Website LinkedIn All Job Openings Staff Fullstack Engineer focused on developing in-product insights on GitLab's Data Insights Platform. Collaborate closely with Product, Design, and backend teams to enhance data delivery. 🇮🇳 India – Remote 💰 Secondary Market on 2020-11 ⏰ Full Time 🔴 Lead 🚰 Data Engineer BigQuery Node.js Ruby ServiceNow Go Staff Fullstack Engineer – Data Products 🕒 4 days ago GitLab 1001 - 5000 🤖 Artificial Intelligence 🏢 Enterprise ☁️ SaaS Website LinkedIn All Job Openings Staff Fullstack Engineer developing in-product insights and solutions at GitLab. Collaborating across teams to create data-driven products and improve software delivery intelligence. 🇮🇳 India – Remote 💰 Secondary Market on 2020-11 ⏰ Full Time 🔴 Lead 🚰 Data Engineer BigQuery Node.js Ruby ServiceNow Go Data Engineer 🕒 4 days ago MediaRadar, Inc. 201 - 500 ☁️ SaaS Website LinkedIn All Job Openings Data Engineer role focused on designing, building, and operating data pipelines. Collaborating with teams across North America and India for a data delivery platform. 🇮🇳 India – Remote ⏰ Full Time 🟠 Senior 🔴 Lead 🚰 Data Engineer Airflow AWS Azure Cloud ETL Postgres Python RDBMS SQL Data Architect 🕒 5 days ago Weekday (YC W21) 11 - 50 ☁️ SaaS 🎯 Recruiter Website LinkedIn All Job Openings Data Architect for a client in retail, collaborating on data initiatives and scalable solutions. Role entails technical leadership and project execution in a remote setting. 🇮🇳 India – Remote ⏰ Full Time 🟠 Senior 🔴 Lead 🚰 Data Engineer Python SQL Director – Data Engineering 🕒 July 3 phData 201 - 500 🤖 Artificial Intelligence ☁️ SaaS 🏢 Enterprise Website LinkedIn All Job Openings Director in data engineering at phData, guiding strategic customer accounts and technical leadership. Leadership role focusing on delivery excellence and partnership revenue growth. 🇮🇳 India – Remote 💰 $2.5M Seed Round on 2018-03 ⏰ Full Time 🔴 Lead 🚰 Data Engineer AWS Azure Cloud Google Cloud Platform Python SQL View More Data Engineer Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Privacy policy Terms of service Job board SEO course AI Apply Copilot OpenClaw job finder Find jobs using your resume Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs