Enterprise Data Architect

Job title: Enterprise Data Architect
Location : Remote








JD:
The Enterprise Data Architect is responsible for defining and driving enterprise data modernization strategies, enabling the successful migration of legacy data platforms such as SQL Server and IBM DB2 to modern cloud-based analytics platforms including Snowflake and Databricks. The role provides strategic and technical leadership for designing scalable, secure, and high-performing data architectures, ensuring alignment with business objectives, governance standards, and future-state analytics requirements.




The architect leads assessment, planning, implementation, and optimization efforts, proposing migration roadmaps, architectural patterns, and best practices to accelerate enterprise cloud adoption while minimizing business disruption.




Expected Experience: 8-15 Years




Key Responsibilities
Assess and analyze existing enterprise data ecosystems, including SQL Server, DB2, data warehouses, operational systems, reporting platforms, and downstream data consumers.
Define target-state cloud data architecture leveraging Snowflake, Databricks, Azure Data Lake, and modern data engineering frameworks to support analytics, AI/ML, reporting, and operational workloads.
Develop migration strategies, roadmaps, and implementation plans for transitioning legacy databases, ETL processes, data marts, and reporting solutions to cloud-native platforms.
Design scalable data models, data integration patterns, metadata frameworks, and data governance standards to ensure consistency, performance, and compliance.
Lead database modernization initiatives including schema conversion, workload assessment, performance optimization, code remediation, and platform rationalization.
Establish enterprise data architecture standards, reference architectures, and best practices for data ingestion, transformation, storage, security, and consumption.
Collaborate with business stakeholders, application teams, data engineers, and cloud architects to align migration approaches with business priorities and technical constraints.
Identify dependencies, data quality risks, integration challenges, and operational impacts associated with migration activities and define mitigation strategies.
Provide architecture guidance for implementing cloud-native data pipelines using Databricks, Spark, ELT/ETL frameworks, and orchestration tools.
Drive performance tuning, scalability planning, cost optimization, disaster recovery, and security best practices across Snowflake and Databricks environments.
Evaluate and recommend migration tools, automation frameworks, and modernization accelerators to reduce implementation timelines and migration risks.
Lead proof-of-concepts, architecture reviews, and governance forums while mentoring delivery teams on cloud data architecture best practices.
Key Skills & Experience
Extensive experience in Enterprise Data Architecture, Data Warehousing, and Data Platform Modernization.
Strong expertise in SQL Server, IBM DB2, relational databases, dimensional modeling, and enterprise data management.
Hands-on experience architecting and implementing migrations from SQL Server, DB2, Oracle, Teradata, or other legacy platforms to Snowflake and Databricks.
Deep understanding of cloud data platforms including Snowflake, Databricks, Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), AWS, and related cloud services.
Experience defining migration strategies, data modernization roadmaps, phased implementation approaches, and cloud adoption frameworks.
Expertise in data modeling, metadata management, master data management, data quality, and data governance.
Strong knowledge of Spark, Delta Lake, data lakehouse architecture, ELT/ETL frameworks, and modern data engineering practices.
Experience with performance tuning, workload optimization, security architecture, RBAC, encryption, and compliance requirements.
Ability to evaluate business requirements and translate them into scalable, secure, and future-ready cloud data architectures.
Strong stakeholder management, consulting, and communication skills with proven experience presenting architecture strategies and recommendations to executive leadership.
Preferred Technologies
Snowflake
Databricks
Azure Data Lake Storage (ADLS)
Azure Data Factory (ADF)
DBT
Apache Spark
SQL Server
IBM DB2
Oracle
Power BI
Azure/AWS Cloud Platforms
Git, Azure DevOps, CI/CD Pipelines