Snowflake Data Architect

Zohorecruit; Hyderabad; On-site; INR 300,000 - 600,000; Full time

Job summary

Algoleap Technologies Pvt Ltd seeks a seasoned data architecture leader to define end-to-end Snowflake architecture for scalable, secure, and AI-ready CRE data platforms. The role combines hands-on engineering with strategic governance and cross-functional leadership.

You will guide multi-environment deployments, data modeling, and integration with CRM feeds, BI tools, and downstream systems, while ensuring cost efficiency and security.

Qualifications

• 15+ years of experience in data architecture, data engineering, or enterprise data platforms.
• Hands-on Snowflake experience with solution design and leadership in modern data platforms.
• Strong governance, security, and compliance awareness across schemas and data sharing.
• Excellent communication with technical and non-technical stakeholders.

Responsibilities

• Own end-to-end Snowflake architecture across multi-environment stacks.
• Design data layering models for CRE domains (property, lease, sales, etc.).
• Define semantic views/models for BI and LLM access.
• Lead ETL/ELT pipelines, ingestion from CRM and third-party sources.

Skills

Snowflake

Data architecture

Leadership

SQL

Python

Education

Bachelor's or Master’s in CS/IT/Engineering

Tools

dbt

Airflow

Snowpark

Terraform

Job description

Algoleap Technologies Pvt Ltd | Full time

The ideal candidate will lead end-to-end architecture/solution designcentered on Snowflake, enabling scalable, secure, and AI-ready data platformsfor commercial real estate business and its stakeholders. This role requirestechnical expertise (includes analytics and AI tech stacks), domainunderstanding, executive communication capability, and hands-on leadership incomplex modernization initiatives and product platforms.

Key Responsibilities

• Own the end-to-end Snowflake architecture: account/org topology,databases, schemas, warehouses, and multi-environment (dev/UAT/prod) strategy.
• Design the data layering model (raw → staging/EDP → curated/semantic marts)for CRE domains: property, lease, availability, sales, organization, contact.
• Define semantic views / semantic models over business data so BI andLLM/NL-query tools consume governed, business-friendly entities.
• Set warehouse sizing, scaling, and workload isolation (ETL vs BI vsdata-science vs app-serving).
• Establish naming conventions, object ownership, and referencearchitecture patterns.

Data Modeling & Engineering Leadership

• Define dimensional/data-vault or hybrid models and canonical join keys(e.g., a single property-building spine) to prevent fanout acrossproperty/lease/sale subject areas.
• Guide ETL/ELT pipeline design (batch and streaming), including ingestionfrom CRM (Salesforce), market feeds, and third-party CRE sources.
• Lead use of dynamic tables, streams, tasks, and Snowpark fortransformation and incremental processing.
• Set standards for data typing/casting, deduplication, and handling ofwide, loosely-typed source tables.

Data Governance, Security & Compliance

• Architect RBAC: role hierarchy, functional/access roles, and segregationof duties between policy creation and application.
• Implement column-level security (masking), row-level security (rowaccess policies), object tagging, tag-based masking, and sensitive-dataclassification for PII (tenant/landlord/contact data, deal financials).
• Define data quality monitoring (DMFs, expectations, anomaly detection)and auditing via Access History / Object Dependencies.
• Align with regulatory/privacy requirements (GDPR/CCPA, clientconfidentiality, NDA-bound deal data) and enforce network/egress policies.
• Design integration patterns between Snowflake and downstream stores(e.g., Postgres), apps (Streamlit/React), and BI tools.
• Govern external connectivity: External Access Integrations, APIingestion, Secure Data Sharing, and provider/consumer data exchange withbrokers/partners.
• Oversee geospatial and market-data enrichment pipelines (propertycoordinates, geocoding done upstream of egress-restricted layers).

Performance, Cost & Reliability (FinOps)

• Optimize query performance: clustering keys, search optimization,pruning, and result/metadata caching.
• Own cost governance: warehouse auto-suspend/resume, resource monitors,budgets, and credit-consumption attribution by cost center/project via tags.
• Define SLAs, monitoring, alerting, and capacity planning; trackserverless (DMF/Snowpark) spend.

AI / Analytics Enablement

• Enable natural-language querying and analytics on CRE data throughsemantic models and (where in-boundary) Cortex.
• Partner with data science on feature stores, model data access, andgoverned access to sensitive attributes.
• Ensure LLM/agent access respects masking, row policies, and agent-awarecontrols.

DevOps, CI/CD & Operations

• Establish Infrastructure-as-Code (schemachange/Terramform/dbt) andGit-based deployment for Snowflake objects and semantic models.
• Define environment promotion, cloning strategy for test data, andrelease/rollback processes.
• Implement observability (query history, account usage views) andoperational runbooks.
• Set the Snowflake roadmap and reference standards; evaluate new featuresand editions for adoption.
• Act as design authority: review designs, mentor engineers, and enforcebest practices.
• Translate CRE business needs (brokerage, valuations, capital markets,property management) into platform capabilities.
• Partner with business, security, and infra leaders; present trade-offs(e.g., direct-Snowflake vs replicated-store architectures) and managevendor/partner relationships.

Key Qualifications Experience: 15+years of overall experience in data architecture, data engineering, orenterprise data platforms, with substantial hands-on Snowflake experience.Proven ability to lead solution design, data modelling, integration, andimplementation of scalable enterprise platforms.

Education: Bachelor’sor Master’s degree in Computer Science, Information Technology, Engineering, ora related field. Relevant Snowflake, cloud, or data architecture certificationsare preferred.

SQL, Python, andPerformance Optimization: Advanced SQL skills covering complexqueries, stored procedures, incremental processing, and query tuning. StrongPython experience for data processing, API integration, and automation. Abilityto analyze query profiles, optimize warehouse usage, and balance performancewith cost.

Core Snowflake Expertise: Hands-onexpertise with Snowflake key features including Account/warehouse/databasedesign, RBAC, resource monitors, multi-cluster warehouses. Dynamic tables,streams, tasks, and Snowpark (Python), semantic views/models. Secure Data Sharing,cloning, Time Travel, replication/failover. Snowflake governance suite: maskingpolicies, row access policies, object tagging, tag-based masking, dataclassification, data quality (DMFs), Access History, Object Dependencies. Cost/performancetuning: clustering, search optimization, pruning, caching, credit attribution.

Data Modeling &Engineering : Strongdimensional modeling, Data Vault, and medallion/layered architecture patterns. ExpertSQL and performance tuning; handling wide, loosely-typed source tables(casting, dedup, canonical keys to avoid fanout). ELT/ETL design; experiencewith dbt and orchestration (Airflow/dbt Cloud/native tasks). CRE-relevantmodeling: property/building spine, lease/availability/sales subject areas, CRM(Salesforce) integration.

Security, Governance& Compliance : Deep RBAC design and segregation-of-duties modeling.PII protection for tenant/landlord/contact and deal-financial data; GDPR/CCPAand client-confidentiality/NDA handling. Network security concepts: networkpolicies, PrivateLink, External Access Integrations, egress controls.

DevOps / CI-CD / IaC : Git-baseddeployment and Infrastructure-as-Code for Snowflake (schemachange, Terraform,dbt). CI/CD pipelines (Azure DevOps/GitHub Actions), environment promotion,rollback, and test-data cloning. Observability via Account Usage/InformationSchema, logging, and alerting.

Cloud & Ecosystem : Strongon at least one cloud (Azure preferred if deploying to Azure VMs/CICD, elseAWS/GCP): storage, networking, VMs, key vaults, identity. Familiarity withcontainerization (Docker) and, ideally, Snowpark Container Services.

AI / Advanced Analytics(differentiator) : Experience enabling natural-language querying /semantic layers and governed LLM access. Snowflake Cortex and feature-store/MLdata-access patterns; agent-aware security controls.

PersonalStrengths

Leadership& Soft Skills : Design-authority experience: designreviews, standards enforcement, mentoring engineers. Stakeholder managementacross business (brokerage, valuations, capital markets, property management),security, and infra. Ability to communicate architecture trade-offs and costimplications to technical and non-technical audiences. FinOps mindset andstrong documentation discipline.

Communication: Abilityto explain architecture, governance, security, and AI concepts clearly totechnical teams and business stakeholders.

StakeholderManagement: Ability to collaborate with data owners, security teams, applicationteams, and business leaders to align requirements and resolve priorities.

ArchitecturalLeadership: Ability to define standards, evaluate design decisions, mentorengineers, and guide teams toward secure and maintainable solutions.

DeliveryManagement: Ability to manage multiple initiatives, dependencies, and timelinesacross distributed teams.

Problem-Solving: Stronganalytical judgment, with the ability to clarify ambiguous requirements,identify risks, and recommend practical solutions.