Responsibilities
- Design, build, and optimize enterprise-scale Snowflake environments, including database architecture, schema design, data modeling, and performance tuning across large and complex datasets.
- Serve as the internal and client-facing Snowflake subject matter expert — defining standards, best practices, and governance frameworks for Snowflake implementation and ongoing operations.
- Lead the design and delivery of end-to-end data pipelines into and out of Snowflake, including ingestion, transformation, and consumption layers, leveraging Snowflake-native capabilities (Streams, Tasks, Dynamic Tables, Snowpipe) wherever appropriate.
- Architect and implement Snowflake data sharing, data marketplace, and cross-cloud/cross-region replication strategies for client environments.
- Define and enforce Snowflake security architecture including role-based access control (RBAC), column-level and row-level security, data masking policies, and network policies.
- Lead Snowflake performance optimization activities including clustering keys, materialized views, query profiling, warehouse sizing, and cost governance.
- Drive adoption of Snowflake best practices across client delivery teams, including query optimization, warehousing strategy, and data lifecycle management.
- Translate business and technical requirements into Snowflake-first solution designs, defining required work packages, resourcing, and delivery approach.
- Define and socialize technical approaches for Snowflake-based implementations including data migration strategies, SDLC standards, and integration patterns — influencing client teams toward best practice.
- Lead and mentor a team of data engineers, providing technical direction and code/design review within a Snowflake-centric delivery model.
- Present solution designs, architecture options, and delivery recommendations to business and technology stakeholders at all levels.
- Contribute to Alpha's internal Snowflake IP, accelerators, and proposition development.
- Participate in project team meetings and communicate effectively across internal and client peers, architects, analysts, project managers, and technology teams.
Requirements
- Bachelor's degree in a related field and at least 5 years of data engineering experience, with a minimum of 3 years of hands-on Snowflake implementation experience.
- Snowflake certification(s): SnowPro Core at minimum; SnowPro Advanced: Data Engineer or Architect strongly preferred.
- Familiarity across the Snowflake platform including: Virtual Warehouses, Snowpipe, Streams & Tasks, Dynamic Tables, Data Sharing, Marketplace, Time Travel, Fail-safe, Zero-Copy Cloning, and Snowflake Cortex.
- Proven experience designing and implementing Snowflake security models, like RBAC, data masking, row-level security, and network policy configuration.
- Strong experience with Snowflake performance tuning, like query optimization, clustering strategy, materialized views, warehouse rightsizing, and credit cost management.
- Experience integrating Snowflake with modern orchestration and transformation tools, particularly dbt (data build tool), which is strongly preferred.
- Experience with Snowflake-compatible ingestion and pipeline tooling including Snowpipe, Kafka connectors, Fivetran, Airbyte, or similar.
- Proficiency in SQL at an advanced level and Python for data engineering workflows within Snowflake (Snowpark preferred).
- Experience with cloud platforms (Azure or AWS preferred).
- Experience managing delivery using Agile or similar methodologies.
- Ability to lead cross-functional teams and manage stakeholder expectations at senior levels.
Nice to Have
- Previous experience at a global consulting firm is preferred.
- Experience with Snowflake's AI/ML capabilities including Snowflake Cortex, ML Functions, or Document AI
- Familiarity with Snowflake Native Apps framework and Streamlit-in-Snowflake
- Exposure to complementary tooling in the modern data stack: Databricks, Azure Data Factory, or AWS Glue for hybrid pipeline patterns
- Experience with data governance platforms that integrate with Snowflake (e.g., Alation, Collibra, or Atlan)
- Python-based ML/AI experience (scikit-learn, pandas) for Snowpark-based model development
Benefits
- 25 days of annual paid time off (accrued), in addition to paid holidays
- 5 days of paid training time for continuing education/professional certifications
- Reimbursement for commuting, mobile phone, and home internet expenses
- Supplemented medical, dental and vision coverage
- 401k matching
Additional Information
- Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. Alpha will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)
- All Alpha team members must pass thorough background checks, including fraud prevention initiatives like physical location verifications.
- Team members are expected to be available from 8:30am - 5:30pm EST, Monday - Friday.
- Infrequent travel to client sites may be required.
