Data Integration
6 days ago
Job Description – Data Integration & Architecture Engineer
Location:
Noida
Team:
Platform Engineering – RevAi Pro
Type:
Full-time
About Us
Crenovent Technologies is building
RevAi Pro
, a next-gen revenue operations platform that unifies data, AI agents, and SaaS workflows across industries (SaaS, Banking, Insurance, E-commerce, and Financial Services). Our platform uses
Azure Fabric + PostgreSQL + pgvector
to power near real-time revenue intelligence with deep compliance, governance, and multi-tenancy at its core.
As part of our early engineering team, you'll work on the
foundational data architecture
that powers everything from AI meeting assistants to compensation modelling.
The Role
We are looking for a
Data Integration & Architecture Engineer
who will design and operate the pipelines that unify
CRM, billing, support, and SaaS app data
into our Azure-native data fabric. You'll own the
Bronze → Silver → Gold transformations, Fabric → Postgres egress flows, and tenant-level governance models
.
This role sits at the intersection of
data engineering and platform architecture
— perfect for someone who enjoys solving complex data puzzles and wants to grow into a
Lead Data Architect
role.
What You'll Do
- Build ingestion pipelines
(CDC, batch, webhook, file-based) from CRMs (Salesforce, Dynamics, HubSpot), billing systems (Stripe, Zuora), and support tools (Zendesk, JSM) into
Azure Fabric Bronze/Silver layers
. - Curate standardized models
in Fabric Silver → Gold using Canonical RevAi Schema (CRS), including SCD2 handling, PII tagging, and business-rule conformance. - Operate low-latency egress pipelines
from Fabric → Postgres (staging → ext_* → app consumption), ensuring subsecond query performance for AI agents. - Implement tenant isolation
via RLS in Postgres and Purview policies in Fabric, ensuring strict multi-tenancy and compliance with residency rules. - Own observability & SLAs
: freshness checks, rowcount anomaly detection, and DQ tests across Bronze/Silver/Gold. - Contribute to FinOps dashboards
by instrumenting pipeline cost metrics, cache hit rates, and egress efficiency. - Collaborate with AI engineers
to ensure pgvector embeddings and agent run data integrate seamlessly into the operational data store. - Write runbooks for DR/retention/erasure, and actively participate in quarterly pen-test preparations.
What We're Looking For
Must-Have Skills:
- 2–4 years in
data engineering / integration roles
. - Hands-on with
Azure Data Factory, Azure Fabric (OneLake/Lakehouse), or equivalent (Databricks/Snowflake acceptable)
. - Strong SQL and
PostgreSQL experience
(MERGE, staging, RLS, partitioning). - Experience with
CDC, batch ingestion, or event streaming
(Airflow, dbt, Kafka, or Fabric pipelines). - Comfort with
data governance concepts
(Purview, PII tagging, masked views, data lineage).
Nice-to-Have Skills:
- Knowledge of
pgvector, embeddings, or AI data models
. - Prior exposure to
multi-tenant SaaS architectures
. - Experience with
observability tooling
(freshness checks, data quality gates, anomaly detection). - Familiarity with
FinOps or cost-optimization in data pipelines
.
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