16 days ago
Pune, IndiaSenior
Responsibilities
- Assess data feasibility and readiness for AI use cases, including sources, ownership, volumes, quality, access paths, gaps, and remediation options.
- Build and operate incremental and event-driven pipelines, connectors, and warehouse integrations for the AI platform and production use cases.
- Model governed business entities, metrics, semantic layers, and retrieval-ready knowledge sources for agents.
- Implement user-scoped access, row- and column-level security, data classification, masking, residency controls, lineage, and audit evidence.
- Own production data freshness and quality monitoring, alerting, schema-change recovery, and processing, storage, and embedding cost controls.
- Create reusable data products, connectors, semantic models, and golden datasets for retrieval and answer-quality testing.
Requirements
- 8+ years of data engineering experience, including at least 3 years building data for production ML, analytics, or Gen AI products.
- Strong SQL and Python skills with practical pipeline orchestration experience using tools such as Airflow, dbt, or AWS Glue.
- Experience with Azure, AWS data services such as S3, Glue, Redshift, and RDS, and/or Google BigQuery.
- Hands-on semantic or dimensional modeling experience with technologies such as Cube, dbt Semantic Layer, LookML, or Power BI semantic models.
- Experience with change data capture, webhooks or streaming, incremental ingestion, deletions, and late-arriving data.
- Experience preparing documents for retrieval, designing metadata, and using hybrid or vector search technologies such as OpenSearch, Elasticsearch, or pgvector.
- Practical knowledge of role-based access, row- and column-level security, personal data handling, and cloud identity and access management.
- Experience integrating enterprise SaaS through APIs, including CRM and Atlassian REST APIs.
- Experience with data quality tests, freshness and quality monitoring, and service-level targets for data.
- Strong communication skills for explaining data capabilities and limitations to data owners and business teams.
- Preferred experience with sales and customer data, support and engineering knowledge data, ERP or manufacturing data, or Progress OpenEdge.
- Preferred experience with enterprise RAG or AI platforms, exposing data to agents through APIs or MCP tools, system integrators, central data teams, cross-time-zone collaboration, and enterprise B2B SaaS.
Benefits
- Health and well-being programs supporting work-life balance.
- Opportunity to join a growing business undergoing expansion and transformation.
- Collaborative culture with opportunities for idea-sharing and professional growth.
- Flexible hybrid position based in Pune, requiring 3–4 days of in-office collaboration per week.
Categories
Data Engineering
About QAD, Inc.
QAD builds cloud-based ERP and supply chain software for manufacturing companies, with offerings like QAD Adaptive ERP and the Redzone Connected Workforce platform, sold primarily by subscription with professional services. Its products target mid-market firms across automotive, industrial, food & beverage, life sciences, and consumer goods, embedding workflow and shop-floor capabilities. Founded in 1979 and headquartered in Miami, QAD is privately held and owned by Thoma Bravo.