Accountabilities:

Design end-to-end data and analytics architectures on Snowflake, covering data ingestion, transformation, semantic layers, business intelligence, and AI applications.

Lead migrations from legacy data platforms, including Oracle, Teradata, Netezza, SQL Server, and Hadoop, overseeing assessments, migration strategies, and cutover planning.

Architect and supervise AI and Generative AI solutions using Snowflake Cortex tools, including Cortex AI, Cortex Analyst, and Cortex Search.

Establish technical standards and best practices for data modeling, dbt development, performance optimization, cost management, security, and governance.

Act as the senior technical escalation point for complex client challenges.

Lead, mentor, and develop Data Engineers, Analytics Engineers, BI Developers, and Consultants through regular feedback, career planning, and technical guidance.

Conduct code and architecture reviews to maintain consistent delivery quality and engineering standards.

Partner with recruitment teams on sourcing, screening, and interviewing candidates to support team growth.

Translate business objectives into analytics roadmaps, KPIs, and measurable outcomes.

Oversee multiple client engagements, ensuring effective management of scope, timelines, risks, and delivery quality.

Advise client technical leaders and executives, presenting findings, recommendations, and solution architectures.

Ensure dashboards, data products, and analytical models are adopted and support informed business decisions.

Collaborate with Sales and Account teams on discovery, solution design, technical assessments, effort estimation, and pricing.

Develop and review Statements of Work (SOWs) and technical proposals.

Create reusable accelerators, frameworks, and delivery methodologies to improve project execution.

Represent the organization in client workshops, partner events, and relevant Snowflake ecosystem activities.

Requirements

12+ years of experience in data engineering, analytics, or business intelligence, including significant client-facing experience in consulting, pre-sales, or post-sales environments.

At least 4 years of experience leading technical teams, with a proven ability to mentor and develop engineering professionals.

Deep hands-on expertise in Snowflake architecture, performance tuning, and cost optimization.

Expert-level SQL skills and working proficiency in Python.

Strong experience with dbt and modern data stack technologies such as Fivetran, Matillion, Airflow, or similar tools.

Experience with legacy data warehouse platforms, including Oracle, Teradata, Netezza, and SQL Server, as well as enterprise migration projects.

Practical experience with BI tools such as Power BI, Tableau, Sigma, or Looker.

Proven ability to scope projects, estimate delivery effort, and prepare Statements of Work.

Experience designing and delivering enterprise AI or Generative AI solutions.

Excellent communication and presentation skills, with the ability to engage both technical and executive audiences through architecture workshops, whiteboard sessions, and formal presentations.

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related discipline, or equivalent professional experience.

Preferred qualifications

Snowflake SnowPro Advanced certification in Architecture or Data Engineering.

Hands-on experience with Snowflake Cortex, Snowpark, or Streamlit in Snowflake.

Cloud platform experience across AWS, Azure, or Google Cloud Platform (GCP).

Knowledge of data governance, data quality, and semantic layer design.

Previous experience in a data consulting firm or within the Snowflake partner ecosystem.

Industry experience in financial services, healthcare, retail, or manufacturing.

Benefits

Fully remote work arrangement.

Opportunity to lead enterprise-scale data modernization, analytics, and AI initiatives.

Exposure to diverse client engagements and complex technical challenges.

Opportunity to develop high-performing technical teams and influence engineering practices.

Involvement in pre-sales, solution strategy, and the development of reusable technical assets.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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