Senior Data Engineer

1. Deployment & Infrastructure Engineering

• Deploy EXLdata.ai in client-owned AWS/Azure/GCP environments.
• Configure networking, security, CI/CD, Kubernetes, API gateways, and identity integration.
• Troubleshoot environment, infra, IAM, and pipeline-related issues.
• Lead cloud-level optimizations (scaling, cost, performance tuning).

2. Data Engineering & Pipeline Enablement

• Build, customize, and optimize data pipelines using PySpark, SQL, Databricks, Snowflake, or native hyperscaler data services.
• Integrate platform agents into client workflows (Data Migration, DQ, DataOps, Annotation).
• Assist client SMEs in onboarding data sources, targets, and transformations.

3. Value Realization & Client Enablement

• Serve as the technical anchor for first-of-kind deployments at each client.
• Ensure clients see measurable value from agent-driven automation (SLA reduction, pipeline acceleration, DQ uplift, migration speed).
• Provide hands-on support across discovery, configuration, runbooks, and UAT.

4. GenAI Agent Integration

• Work with product engineering on integrating new GenAI agents into client pipelines.
• Tailor agent behaviors, triggers, and workflows for domain-specific use cases.
• Share field insights that shape our agent roadmap.

5. Product Innovation & Feedback Loop

• Act as the “voice of the customer” for the EXLdata.ai product team.
• Identify enhancements, feature gaps, and new accelerator ideas.
• Participate in internal sprints, tooling improvements, and platform hardening.

6. Managed Service / White-Glove Model

• Support deployments in EXL-hosted private cloud environments.
• Serve as the first line of operational excellence for premium clients.
  • Lead operational reliability, monitoring, and support SLAs.