Senior Snowflake Architect

Ascendion Engineering; Chennai District, Bengaluru, Pune District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Ascendion Engineering seeks an experienced Data Platform Architect to own end-to-end Snowflake architecture for enterprise migration and modernization. You will lead assessments of legacy estates, define migration patterns, and design robust ELT pipelines using Snowflake tools.

The role demands strong SQL, Python, and cloud experience, with leadership across delivery pods. The ideal candidate will drive pre-sales activities, establish governance patterns, and ensure zero data loss during

Qualifications

• 8 to 12 years in data warehousing, data engineering, or analytics platform architecture
• Hands-on Snowflake delivery experience (at least 4 years)
• Snowflake mastery: RBAC, resource monitors, micro-partitioning, clustering, time travel, and secure data sharing
• Strong SQL and Python skills; production experience with Snowpark, Airflow, and cloud-native ingestion tools
• Hands-on cloud architecture experience on AWS/Azure/GCP including IAM, networking, storage, and key management
• Governance and security familiarity: masking, row-level security, tagging, and data catalog integrations
• FinOps: cost-optimized Snowflake deployments, warehouse sizing, workload isolation, and chargeback models
• Consulting skills: client communication, SOW writing, estimations, architecture documents
• Certification: SnowPro Core required

Responsibilities

• Own end-to-end Snowflake architecture for enterprise migrations and modernization
• Lead assessments of legacy data estates and design migration waves
• Define migration patterns and select approaches per workload based on TCO and value
• Architect ELT pipelines with Snowflake tooling and establish project structure and CI/CD
• Design ingestion and transformation frameworks for batch and streaming sources
• Provide technical leadership to delivery pods (6–20 engineers)
• Drive automation of SQL conversion, data validation, and reconciliation
• Conduct architecture and code reviews and enforce standards
• Own production cutover planning, rollback, and hypercare
• Support pre-sales—workshops, RFPs, estimations, and SOWs for Snowflake opportunities

Skills

Snowflake architecture

SQL

Python

Communication

Cloud architecture

FinOps

Governance & security

SOW/ estimations

Tools

Snowflake

dbt

Snowpark

Airflow

Fivetran

Matillion

Informatica IDMC

ADF

AWS Glue

Job description

Key Responsibilities

• Own end-to-end target-state Snowflake architecture for enterprise migration and modernization engagements, including landing zone, RBAC, data sharing, and multi-account design.
• Lead current-state assessments of legacy Teradata, Oracle, Netezza, SQL Server, and Hadoop estates; build workload heat maps and migration wave plans.
• Define migration patterns (lift-and-shift, re-platform, re-engineer) and decide the right approach per workload based on TCO, risk, and business value.
• Architect ELT pipelines on Snowflake using dbt or comparable transformation tooling — establish project structure, model layering (staging, intermediate, marts), testing, documentation, and CI/CD.
• Design ingestion and transformation frameworks using Snowpark, Streams & Tasks, Dynamic Tables, and Snowpipe for batch, micro-batch, and streaming sources.
• Provide technical leadership to delivery pods of 6 to 20 engineers across data engineering, SQL conversion, ELT modeling, testing, and DevOps tracks.
• Drive automation of SQL conversion, data validation, and reconciliation using Snowflake-native tooling and accelerators such as SnowConvert, Bladebridge, or Datametica.
• Conduct architecture and code reviews; enforce engineering standards, naming conventions, and reusable patterns across ELT projects.
• Own production cutover planning, rollback strategy, and hypercare — ensuring zero data loss and minimal business disruption.
• Support pre‑sales — lead solution workshops, RFP responses, estimations, and SOW construction for qualified Snowflake opportunities.

Must‑Have Qualifications

• Experience: 8 to 12 years in data warehousing, data engineering, or analytics platform architecture, with at least 4 years hands‑on Snowflake delivery.
• Migration depth: Led at least 2 end‑to‑end migrations from a legacy MPP/EDW (Teradata, Netezza, Exadata, SQL Server, or Hadoop) to Snowflake at enterprise scale.
• Snowflake mastery: Strong command of virtual warehouses, RBAC, resource monitors, micro‑partitioning, clustering, query profile analysis, time travel, zero‑copy clone, secure data sharing, and replication/failover.
• Data engineering: Expert SQL plus working proficiency in Python; production experience with Snowpark, Airflow, and at least one cloud‑native ingestion tool (Fivetran, Matillion, Informatica IDMC, ADF, AWS Glue).
• Cloud fluency: Hands‑on architecture experience on at least one of AWS, Azure, or GCP — including IAM, networking (PrivateLink), storage, and key management interplay with Snowflake.
• Governance & security: Deep familiarity with data governance constructs — masking policies, row access policies, tagging, object dependencies, and integration with Collibra, Alation, or Atlan.
• FinOps: Demonstrated ability to design and operate cost‑optimized Snowflake deployments — warehouse sizing strategy, workload isolation, query tuning, and chargeback models.
• Consulting craft: Strong written and verbal communication; comfort engaging with senior client stakeholders; experience writing SOWs, estimations, and architecture documents to publication quality.
• Certification: SnowPro Core certification required.

Nice‑to‑Have

• SnowPro Advanced: Architect certification.
• Hands‑on experience with dbt (dbt Core or dbt Cloud) on Snowflake — model layering, macros, tests, snapshots, and CI/CD; or equivalent experience with similar ELT tooling such as Coalesce, Matillion, or Informatica IDMC.
• Experience with Snowflake Cortex (LLM functions, Cortex Search, Cortex Analyst) for GenAI use cases.
• Hands‑on with Apache Iceberg or open‑table‑format interoperability patterns.
• Exposure to streaming architectures using Kafka, Kinesis, Snowpipe Streaming, or Dynamic Tables.
• Industry depth in one or more of Banking & Financial Services, Healthcare & Life Sciences, Retail & CPG, or Manufacturing.
• Prior experience working in a Snowflake Premier or Elite Partner organization.