Data Architect

Greetings from LTM!

Hope you are doing good. We are hiring Senior Specialist - Architecture to join our digital engineering team.

Who are we?

LTM — a Larsen & Toubro company — is an AI-centric global technology services company and the Business Creativity partner to the world’s largest enterprises. Together with over 87,000 employees across 40 countries and our global network of partners, LTM owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it.

• Design end-to-end data flows covering ingestion, storage, transformation, and consumption.
• Build architectures using Azure Synapse, ADF, Microsoft Fabric, Databricks, and ADLS Gen2.
• Design logical, physical, dimensional, Data Vault, and semantic data models.
• Build Lakehouse and Direct Lake models for Power BI, analytics, and ML workloads.
• Develop reusable data architecture patterns, templates, and metadata-driven frameworks.
• Ensure data models are suitable for AI/ML and GenAI, including feature extraction, embeddings, and contextual reasoning.

• Optimize SQL queries, data pipelines, and Databricks/Synapse workloads for large-scale processing.
• Implement partitioning, indexing, caching, and materialized views.
• Establish performance benchmarks and monitoring across ingestion, transformation, and serving layers.
• Optimize Power BI and Fabric Semantic Models for real-time and ad-hoc analytics.
• Design cost-efficient solutions using serverless computing, caching, and autoscaling.
• Use AI-based monitoring for issues such as query latency, data skew, anomalies, and SLA breaches.

• Implement data governance using Microsoft Purview.
• Automate data cataloging, classification, lineage, and metadata management.
• Define data quality rules, scoring, and anomaly detection.
• Support schema evolution and metadata-driven data onboarding.
• Manage data retention, compliance, stewardship, and accountability.
• Use automation/AI agents for lineage summaries, schema validation, and policy violation detection.

• Implement Zero Trust security, including RBAC, RLS, encryption, and DLP.
• Integrate Microsoft Entra ID, Defender for Cloud, and Purview Data Policies.
• Implement data masking, tokenization, and privacy-preserving techniques.
• Support AI risk assessments covering fairness, transparency, explainability, and data privacy.
• Ensure compliance with frameworks such as GDPR, SOC 2, and HIPAA.

• Build CI/CD pipelines using Azure DevOps, GitHub Actions, or Fabric deployment capabilities.
• Automate testing, code promotion, deployment, and environment provisioning.
• Establish version control and branching standards for ADF, Synapse, Fabric, and Databricks.
• Implement DataOps practices, including continuous integration, testing, and monitoring.
• Build metadata-driven DevOps frameworks with parameterized configurations and reusable scripts.
• Define architecture standards, coding standards, naming conventions, and change-management processes.
• Conduct architecture reviews, performance health checks, and audit-readiness assessments.

• Work with AI/ML teams to build feature stores, model-training pipelines, and MLOps architectures.
• Track lineage across raw data → features → models → predictions.
• Use GenAI for documentation, error detection, and automated pipeline recovery.
• Monitor data drift, model performance, and bias.
• Enable AI-powered prediction and personalization within data products.