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Job Description — AI-Native Engineer (T1 — Data Architect)
1. Role Summary
The T1 AI-Native Data Architect shapes Virtusa's lakehouse, streaming, warehousing, MDM, governance, and ML/GenAI data foundations in an AI-Native model where agents (Claude Code primary, GitHub Copilot / Kiro / custom as alternates) are first-class SDLC contributors. Moves data teams from "pipeline writers" to environment designers accountable for context architecture, validation loops, guardrails, governance, and operating model. Hands-on across lakehouse design, modeling, dbt / Spark tuning, agent frameworks, MCP, and client-facing governance. GitHub Copilot / Kiro equivalents acceptable.
Modeling — Kimball dimensional, Data Vault 2.0, normalized 3NF, medallion
(bronze/silver/gold), semantic / metrics layer; SCD types, slowly-changing dimensions, late-
arriving facts, conformed dimensions.
SQL at expert level across at least one of Snowflake, BigQuery, Databricks SQL,
Synapse / Fabric, Redshift, Postgres — window functions, CTEs, query optimization,
partitioning / clustering, materialized views.
Distributed processing — Apache Spark / PySpark (production-scale), Databricks (Delta
Lake, Unity Catalog, DLT, Workflows), Apache Flink / Beam / Dataflow awareness;
performance tuning (skew, spill, shuffle, broadcast).
Work arrangement
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