Role Summary
Ascendion is hiring a Senior Snowflake Architect to lead the architecture and delivery of complex data platform migration and modernization programs on Snowflake. You will own end-to-end solutioning for client engagements that involve migrating legacy data warehouses (Teradata, Oracle Exadata, Netezza, SQL Server, Hadoop) and ETL platforms (Informatica, DataStage, Ab Initio, SSIS) onto Snowflake, and modernizing transformations using ELT tooling such as dbt.
This is a hands-on, client-facing role. You will partner with pre-sales and delivery teams — shaping proposals, leading discovery workshops, owning target-state architecture, and steering delivery squads to production go-live.
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: 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.
