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Lead Data Engineer And Architect

Role: Lead Data Engineer And Architect; Relevant Experience: At least 8+ years of relevant experience are required; Location: Bengaluru, KA and Coimbatore; Notice period: We are Open Preferred Who can Join as soon as possible; Opportunity: Full time

Role Summary:

We are seeking a Senior Lead Analytics Engineer with deep expertise in Snowflake and dbt to design, build, and govern modern data warehouse frameworks that enable trusted AI, advanced analytics, and BI use cases.

This role goes beyond building pipelines you will define the architectural patterns, data frameworks, and best practices that turn raw data into a scalable, reusable, and business aligned Unified Data Model (UDM) and semantic layer. The ideal candidate has a strong data modeling mindset and understands how architecture decisions directly impact AI readiness, analytics accuracy, and business trust.

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:

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.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Lead Data Engineer And Architect

Job Description

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