Aezion - Lead Data Engineer - Snowflake & DBT

Description :

Key Responsibilities :

Data Architecture & Framework Design :

- Design and build enterprise-grade data warehouse architectures on Snowflake.

Define data frameworks and standards covering :

- Layered modeling (raw, staging, curated, semantic)

- Naming conventions and modeling patterns

- Reusable transformation and metric frameworks

- Establish best practices for scalability, performance, governance, and cost efficiency.

- Ensure architecture supports AI, BI, and self-service analytics consistently.

Data Warehouse, UDM & Semantic Layer :

- Design and maintain Unified Data Models (UDM) aligned to business domains.

- Build robust semantic layers enabling reusable metrics and dimensions.

- Standardize business definitions to support :

- BI reporting

- Advanced analytics

- AI / ML feature consumption

- Ensure models are understandable, extensible, and well-documented.

dbt & Analytics Engineering :

- Lead dbt-based transformation frameworks across the platform.

- Implement and govern dbt best practices:

- Modular model design

- Testing, snapshots, and documentation

- Data lineage and exposures

- Embed data quality, freshness, and validation into the transformation layer.

- Integrate dbt workflows into CI/CD pipelines for repeatable deployments.

AI & BI Enablement :

- Design curated datasets optimized for AI and advanced analytics use cases.

- Enable BI tools (Power BI, Tableau, Looker, etc.) with performant, analytics-ready models.

- Ensure datasets are explainable, traceable, and consistent across consumption layers.

- Collaborate with AI, analytics, and business teams to align data design with use cases.

Leadership & Governance :

- Act as a technical lead and architect for analytics engineering initiatives.

- Mentor engineers and enforce modeling, testing, and documentation standards.

- Drive adoption of data modeling, metric, and semantic best practices enterprise-wide.

- Translate business requirements into scalable, governed data solutions.

Required Qualifications :

- 8+ years of experience in analytics engineering or data engineering.

- Strong hands on experience with Snowflake and dbt.

- Deep expertise in dbt and modern analytics engineering practices.

- Proven experience designing data warehouses, UDMs, and semantic layers.

- Excellent SQL skills with a strong data modeling foundation.

- Experience building architectural frameworks and best practices, not just pipelines.

Preferred Qualifications :

- Strong design and build experience in modern data architecture patterns

- Experience with BI tools and metric/semantic modeling frameworks.

- Experience enabling AI / ML workloads using curated data models

- Excellent communication and data storytelling skills.