Data Integration

4 weeks ago

Noida, Uttar Pradesh, India Crenovent Full time
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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