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SENIOR DATA AND PLATFORM ENGINEER GATEKEEPER SYSTEMS, INC. FOOTHILL RANCH, CA At Gatekeeper Systems, we’re revolutionizing retail loss prevention and customer safety through a powerful combination of physical deterrents and cutting-edge technology—including AI, computer vision, and facial recognition. As a global leader with over 25 years of industry excellence and a growing, diverse team of 500 employees across offices in North America, Europe, Australia, and Asia , we’re driven by innovation, integrity, and impact. Join us and be part of a mission-focused team that’s making a real difference in the future of retail, providing innovative solutions and services that redefine industry standards. THE OPPORTUNITY This is a senior hands-on engineering role at the center of our data platform transformation. You will own the backend data infrastructure — relational database design, cloud data warehouse architecture, and the API layer that connects them to customer-facing products and internal analytics tools. This is not a pure architecture role and not a pure maintenance role. You will design systems and build them. You will mentor developers and review their code. You will triage a customer issue in the morning and design a new data schema in the afternoon. The role rewards engineers who thrive across the full stack of backend data work — from database DDL to API design to cloud infrastructure — and who move between strategic thinking and hands-on execution without friction. What You Will Own Relational Database — Design, Operations, and Reliability Own the operational PostgreSQL database end-to-end: schema design, migration tracking, indexing strategy, connection pooling, high availability configuration, point-in-time recovery, and read replica management on Google Cloud SQL Design and maintain the data models that power product features, customer reporting, device management, alert processing, and LP intelligence workflows Build the new intelligence registry layer — persistent identity records, organizational grouping structures, asset tracking tables, and per-location risk profiles — that enable cross-incident and cross-location analytics for the first time Enforce multi-tenant data isolation: row-level security at the database layer, strict per-tenant query scoping enforced independently of application code Cloud Data Warehouse — Architecture and Analytics Design and build a clean, layered BigQuery data warehouse architecture — replacing a fragmented multi-dataset structure accumulated without a canonical data model — organized into raw ingestion, curated analytics, and pre-aggregated intelligence layers Build and maintain pre-computed analytical views covering cross-location activity patterns, organized retail crime group intelligence, regional trend heatmaps, travel pattern detection, and merchandise theft analytics — enabling LP investigators and directors to operate proactively rather than reactively Own data freshness, quality, and pipeline reliability across all layers — change data capture from the operational database, event stream subscriptions, and scheduled refresh jobs Design and implement a GKS-owned cross-retailer anonymized benchmark dataset — aggregating intervention outcomes and performance metrics across all deployments by store archetype, with strict retailer data separation — the data asset that enables GKS to show any customer how they compare to similar deployments across the network Manage BigQuery cost and performance: partition and cluster strategy, BI Engine reservations, partition filter enforcement, materialized view design API Design and Backend Engineering Design, build, and maintain the API layer that customer applications, internal analytics tools, and LP workflow platforms read from — GraphQL and REST, with performance, security, and scalability owned here Implement and maintain the versioned data contract between the operational database layer and the LP case management platform built by our partner engineering team — ensuring schema changes on either side are governed, tested, and do not produce silent breakage Work with the hardware and firmware engineering teams on the event publication pipeline — device pushout events, task queue publication to downstream services, fan-out architecture for multi-consumer event streams Design API access control — which user roles can access which data, how tenant identity is enforced end-to-end from authentication token through API to database row-level security GCP Infrastructure and DevOps Own GCP data infrastructure as code using Terraform: managed database instances, data warehouse datasets, messaging topics, change data capture streams, serverless compute jobs, IAM bindings, VPC configuration, and secrets management Build and maintain CI/CD pipelines for data platform changes — migration gates, schema validation, deployment promotion through dev, staging, and production environments with automated quality checks GCP security posture: migrate all credentials to Secret Manager, enforce VPC Service Controls, apply per-service least-privilege access, enable audit logging, and build the evidence base needed for SOC 2 compliance GCP cost management across compute, storage, and analytics workloads Customer and Operations Support Serve as the technical escalation point for data platform issues in production — work with the Operations team on customer triages, root cause analysis, and durable fixes that reduce recurring operational load Support the Operations team on BI reporting — help non-engineering team members understand data structures, review and improve analytical queries, and build self-serve analytics foundations that reduce engineering dependency Proactively identify when a schema change, pipeline delay, or performance issue will affect customer-facing products — and surface it before it becomes a support ticket Offshore Engineering and Product Team Collaboration Work with the offshore engineering team on product data requirements — provide technical direction, code review, and mentoring across time zones for data layer integration work on our next-generation experience platform Define the API surface and data models that the experience platform personas consume — ensure access control enforcement at the API layer aligns with data isolation enforcement at the database layer Collaborate with the partner engineering team on LP case management platform integration — boundary contracts, data contracts, versioning, and change governance Mentoring and Technical Leadership Mentor junior developers on the data platform team — code review, architecture guidance, debugging technique, and cloud platform best practices Be the technical anchor for the offshore engineering team on data platform work — design direction, implementation unblocking, and asynchronous work review Guide the Operations team on data literacy — help them understand data structure well enough to build and interpret business reports without engineering involvement for routine requests Leverage Claude AI and other AI coding tools as a productivity standard — not as a pilot but as the baseline expectation for design, research, code generation, and documentation. Model this for the team Must-Have Experience WHAT WE ARE LOOKING FOR 7+ years of hands-on backend data engineering with clear ownership of production systems — not advisory or architecture-only roles Deep PostgreSQL expertise: schema design, query optimization, indexing, migration management, connection pooling, and managed cloud database operations including high availability and point-in-time recovery BigQuery mastery: partitioning and clustering strategy, materialized views, BI Engine, authorized views, row-level security, change data capture integration, and cost control through physical design and slot reservations Python as your primary language — production-quality Python on serverless
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.