Data Architect

Job Description Role: Data Architect Total Experience: 10-15 Years Location: Bhilai/Indore Job Description: 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).