Integration Consultant, Tech

🏢 Gigawatt AI · all Gigawatt AI jobs
📍 United States
📅 Posted 2026-08-08 · via Himalayas
🏷 Integration-Consulting,Data-Engineering,Solutions-Engineering,Technical-Consulting,Enterprise-Integration,Technical-Integration-Consultant,Integrations-Consultant,Integration-Solutions-Consultant,Technical-Consultant-Integration,Technical-Integration-Consulting,Systems-Integration-Consultant,Digital-Integration-Consultant
Apply on original site ↗

Company Overview

Gigawatt is building the AI-native software that runs America’s utilities — a modern, agentic suite spanning customer, revenue, service, and procurement operations. We are live with our first major utility customer and scaling fast. Learn more at .
Job Summary

Gigawatt’s platform is only as valuable as the data feeding it. Before a customer can go live, their source-system data — CIS and billing, meter and interval usage, outage, clearinghouse, and more — has to be mapped, migrated, loaded, validated, and then kept in sync as the platform runs. This role is the hands-on technical person who makes that happen.

As an Integrations Consultant, you own the working-level data-readiness and integration delivery for a customer: you profile and map source data, build and run the migration and conversion loads that stand up each go-live, and build the inbound and outbound integrations that keep data flowing in both directions afterward. You report to the Integrations Director and work within the connector framework and patterns they set, partnering closely with Engineering (who own the core platform and its APIs), Product, and the customer’s data and enterprise-integration teams. The work is cross-module — Customer, Revenue, and Service — with our anchor customer as the proving ground where the approach is hardened and then reused for the customers we sign next. This is the kind of hands-on solutions and data-integration work we are already doing today; we are adding capacity to do more of it, reliably and at scale.

On the inbound side, our approach is a four-pattern, single-replica design — API read, API write, Kafka initial load, and Kafka change-data-capture — moving data from customer source systems through Oracle GoldenGate and Confluent Kafka, via Boomi, into a Gigawatt local replica that feeds the modules. On the outbound side, Gigawatt exposes a rich integration surface — GraphQL, batch, webhook/hook, and event APIs, plus connectors and event streams — so external systems consume Gigawatt’s governed data and react to its events. You build and run both sides for your customer.
Key Responsibilities

-
Own customer data readiness — Profile source systems, define the data each module needs, secure access, and get that data into shape to load — surfacing quality and structure issues early.

-
Build and run migration and conversion loads — Do the source-to-target mapping, run mock and iterative loads with the data team, validate results, and reconcile against the legacy system to stand up each go-live and work through the cleanup that follows.

-
Build inbound integrations — Stand up the four-pattern feeds (API read/write, Kafka initial load, Kafka CDC) through GoldenGate, Confluent, and Boomi into the Gigawatt replica.

-
Build outbound flows — Build the flows that publish Gigawatt data, bills, events, and results back out — for example bill results into the CIS / MACSS, EDI and market transactions, and curated data or regulatory outputs.

-
Own data mapping and quality, both ways — Maintain source-to-target and target-to-source mappings and a validation approach so data lands complete and correct in either direction and gaps are caught before testing.

-
Handle scale and performance — Build loads and syncs that perform against large data volumes and high-row-count tables, and tune them when they don’t.

-
Keep integrations reliable — Wire up triggers and handshakes and put monitoring, alerting, reconciliation, and exception handling in place, so feeds run automatically and failures are caught by alerting rather than by the customer.

-
Work directly with the customer’s data and integration teams — Agree interfaces, source and target access, field-level detail, and testing, API by API.

-
Reuse and contribute to the framework — Build on the shared patterns the Integrations Director sets, and feed reusable connectors and improvements back so each new connection is faster than the last.

-

← All remote jobs