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Sr Platform Architect

Actively Reviewing the Applications

Infobell IT

India, Karnataka Full-Time On-site
Posted 3 days ago • Apply by June 11, 2026

Job Description

Job description

Senior Platform Architect.


Experience: 15+ years

Location: Bangalore

Work Mode: On-site


Immediate joiners preferred.


Interested candidates can send their CV to [email protected]


Roles & Responsibilities

· Own the enterprise data platform vision, roadmap, and reference architecture across ingestion, storage, transformation, and consumption layers.

· Lead architectural decisions for Lakehouse, warehouse, and hybrid platform patterns tied to business objectives.

· Design and govern batch, micro-batch, and real-time streaming pipelines across medallion (bronze/silver/gold) layers.

· Establish enterprise data governance frameworks covering lineage, cataloguing, ownership.

· Embed security-by-design principles - RBAC/ABAC, column/row-level security, encryption, and audit logging across the platform.

· Serve as the primary technical advisor to product, engineering, and business stakeholders on platform capabilities, trade-offs, and roadmap priorities.

· Mentor data engineers, set coding and testing standards, and foster a culture of engineering excellence.

Technical Skills

· Azure: Data Factory, ADLS Gen2, Key Vault, Monitor, DevOps

· Databricks: Unity Catalog, Delta Lake, Lakeflow Connect, Spark Declarative Pipelines, Lakeflow Jobs, Asset Bundles, Auto Loader, Databricks SQL, Spark Structured Streaming

· Data Quality: DLT Expectations, Great Expectations

· Integration & Transformation: dbt, Apache Spark

· Languages & DevOps: Python, SQL, Terraform, Git, CI/CD

Data & Platform Architecting Skills

· Expertise in Kimball dimensional modelling and end-to-end Lakehouse design across ADLS Gen2, Databricks, Unity Catalog, Purview, and Power BI.

· Proficient in Lambda and Lakehouse patterns, idempotent pipeline design, late-arriving data handling, schema evolution, and Delta Lake time travel.

· Platform observability: pipeline monitoring, data quality dashboards, SLA alerting, and incident response.

· Security architecture: zero-trust access, managed identity, Unity Catalog privilege hierarchy, private endpoints, and VNet integration.

· CI/CD for data platforms: environment promotion, automated testing, infrastructure-as-code, and artifact versioning.

· Cloud FinOps: cost governance, reserved capacity planning, and resource optimization.

· Self-healing patterns: automated anomaly detection, pipeline retry/recovery, and data quality circuit breakers.

hashtag


#SeniorHiring hashtag

#ArchitectHiring hashtag

#TechnologyLeadership hashtag

#DataLeader hashtag

#EnterpriseArchitect hashtag

#DigitalTransformation hashtag

#TechStrategy hashtag

#ModernDataStack hashtag

#CloudDataPlatform hashtag

#AzureData hashtag

#DatabricksCommunity hashtag

#UnityCatalog hashtag

#DataLakehouse hashtag

#CloudNative hashtag

#ScalableArchitecture hashtag

#Spark hashtag

#PySpark hashtag

#StructuredStreaming hashtag

#DataPipelines hashtag

#RealTimeData hashtag

#BatchProcessing hashtag

#MedallionArchitecture hashtag

#DimensionalModeling hashtag

#ZeroTrust hashtag

#DataSecurity hashtag

#DataLineage hashtag

#DataQuality hashtag

#RBAC hashtag

#ABAC hashtag

#EnterpriseData hashtag

#CloudCostOptimization hashtag

#FinOpsFoundation hashtag

#CostGovernance


Required Skills

Engineering Git Monitoring Python Apache Spark SQL Audit Terraform Power BI Spark Data Governance Azure Encryption Databricks Unity DevOps CI/CD Automated Testing Testing Lambda Apache Data platform Data quality Governance DBT Auto Anomaly detection Capacity Planning Unity catalog Schema evolution RBAC Work Mode Schema Incident response Data platforms Ingestion Dimensional Modelling Delta VNET Privilege PySpark Dashboards Logging Design Principles Hashtag Self-healing Factory Recovery Pipeline design Detection Enterprise Data ADLS Cloud FinOps Testing Standards Storage Observability Trade Batch Lakehouse Incident Dimensional Vault Time Travel Key Vault Resource optimization Data Factory Structured Streaming Great Expectations
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