Data Architect

Role:

Total Experience:

Location:

We are looking for a Data Architect with10+years of experience in designing, implementing, and governing modern data platforms. The ideal candidate should have strong experience working with enterprise clients, hands-onexpertisein Microsoft Fabric, and the ability to conceptualize and lead end-to-end Data Engineering and AI solution engagements.

This role is both consultative and technical, involving architecture design, solutionroadmapping, client workshops, POC leadership, and guiding teams toward high-quality delivery.

Key Responsibilities

1. Data Architecture & Engineering Leadership

• Design scalable enterprise data architectures includinglakehouse, data warehouse, Fabric-based analytics, and real-time processing layers.
• Architect and implement ingestion, transformation, modeling, governance, and data quality frameworks.
• Build reusable frameworks for metadata-driven pipelines, incremental loads, and large-scale data processing,similar toframeworks highlighted in enterprise-scale work
• Define best practices for data modeling (OLTP/OLAP), data cataloging, security, storage optimization, and cost governance.

2. Microsoft Fabric & Modern Data Stack

• Lead solutionsleveragingMicrosoft Fabric including Lakehouse, Data Factory, Data Pipelines, Power BI,OneLake, Direct Lake, and governance layers.
• Leverage experience with analogous platforms such as Azure Databricks, Synapse, and Data Factory for building high-performance pipelines
• Fabric certification is a strong plus.

3. Consultative Client Engagement

• Run client workshops, requirement discovery sessions, architecture reviews, andmodernizationroadmap discussions.
• Translate business needs into solution blueprints and work with technical teams for implementation.
• Advise clients on modernization strategies such as migrations from legacy systems to cloud platforms,lakehouses, or Fabric-based ecosystems.
• Present architectural options, tradeoffs, cost models, and delivery approaches.

4. POC Leadership & Technical Evangelism

• Lead POCs and accelerated solution pilots focused on Data Engineering, Lakehouse modernization, and AI/ML adoption.
• Work directly with prospects and existing clients todemonstratefeasibility, value realization, and platform readiness.
• Stay updated on emerging trends such as streaming, DLT, governance, feature stores, and GenAI pipeline integration.

5. Hands-on Engineering Capability

• Strongproficiencywith Python, SQL, Spark, Fabric Data Factory, Delta/Parquet-based data processing, and cloud-native orchestration frameworks.
• Experience with enterprise-grade ETL/ELT pipelines (Spark, ADF, Databricks, Airflow,dbt) that handle large-scale volumes
• Ability to get hands-on when needed during architecture validation, POCs, or team escalation scenarios.

6. Governance, Security & Compliance

• Implement data governance, lineage, access controls, quality frameworks, and auditing consistent with enterprise standards.
• Familiarity with governance tools and practices across cloud platforms (Azure Purview, Unity Catalog, RBAC, IAM) as used in past enterprise roles.

7. Team Leadership

• Mentor and guide engineers on architecture patterns, coding practices, cloud/data standards, and modern engineering approaches.
• Lead cross-functional Data Engineering squads through sprints, design sessions, and architecture boards.
• Establish engineering excellence practices across code quality, documentation, testing, and observability.

Required Skills & Experience

• 812 years of hands-on Data Engineering and Data Architecture experience.
• Strong experience working for enterprise clients across domains such as finance, consulting, insurance, retail, or supply chain.
• Deepexpertisein at least one cloud (Azure preferred) withstrongSpark-based engineering background.
• Hands-on skills with Microsoft Fabric (Data Factory, Lakehouse, Direct Lake, Pipelines, Power BI).
• Strong experience with modern data ecosystems: Databricks, Synapse, ADF, Snowflake,BigQuery, Delta Lake, Kafka, APIs, distributed data systems.
• Solid understanding of data modeling, warehousing, and streaming architectures.
• Proven ability to lead client discussions, technical presentations, and architectural whiteboarding sessions.
• Strong problem-solving ability with the capability to design scalable, secure, and cost-optimized systems.
• Ability to work onsite fromBhilaior Indore as needed.

Preferred Qualifications

• Microsoft Fabric certification (or ongoing).
• Databricks or Azure Data Engineering certifications.
• Experience integrating AI/ML or Generative AI pipelines into ETL workflows.
• Experience in leading migrations from legacy systems to modern platforms (Fabric, Databricks, Azure).