Data Architect

Job Description

• Modern data architecture across ingestion, lakehouse/warehouse, semantic/analytics layer, AI/ML integration, and GenAI workloads.


• Cloud-native data platforms such as Azure Synapse / Fabric, Databricks, Snowflake, BigQuery, Redshift or equivalent.


• Lakehouse and medallion patterns, Delta Lake, data warehousing, data marts, and enterprise analytical modeling.


• ETL/ELT and orchestration tools such as Azure Data Factory, Airflow, dbt, AWS Glue, Informatica or equivalent.


• Data modeling across conceptual, logical, and physical models, metadata, lineage, master/reference data, and data quality principles.


• Data governance, privacy, security, compliance, cataloging, and stewardship tools such as Microsoft Purview or Collibra concepts.


• Streaming and integration patterns using Kafka, Event Hubs, APIs, and batch/near-real-time data pipelines.


• Working knowledge of AI/ML, GenAI, RAG, vector databases, and how data platform design enables AI workloads.
  


• Lead technical discovery workshops with business, data, analytics, and IT stakeholders to understand target outcomes and constraints.


• Translate business objectives into target-state data architectures, value-driven solution blueprints, and phased transition roadmaps.


• Design end-to-end modern data platforms including ingestion, lakehouse/warehouse, analytics, AI/ML, and GenAI enablement layers.


• Define reference architectures, integration patterns, data models, data quality controls, governance mechanisms, and security architecture.


• Assess legacy data environments and recommend modernization approaches that balance scalability, cost, performance, and delivery practicality.


• Support proposals, RFIs/RFPs, PoCs, architecture diagrams, cost modeling, sizing, and solution defense sessions.


• Partner with cloud, AI, cybersecurity, application, and delivery teams to ensure architectures are secure, scalable, compliant, and delivery-ready.


• Mentor data engineers and junior architects on architecture patterns, engineering standards, and reusable assets.
  

Must Have Technical/Functional Skills

• Modern data architecture across ingestion, lakehouse/warehouse, semantic/analytics layer, AI/ML integration, and GenAI workloads.


• Cloud-native data platforms such as Azure Synapse / Fabric, Databricks, Snowflake, BigQuery, Redshift or equivalent.


• Lakehouse and medallion patterns, Delta Lake, data warehousing, data marts, and enterprise analytical modeling.


• ETL/ELT and orchestration tools such as Azure Data Factory, Airflow, dbt, AWS Glue, Informatica or equivalent.


• Data modeling across conceptual, logical, and physical models, metadata, lineage, master/reference data, and data quality principles.


• Data governance, privacy, security, compliance, cataloging, and stewardship tools such as Microsoft Purview or Collibra concepts.


• Streaming and integration patterns using Kafka, Event Hubs, APIs, and batch/near-real-time data pipelines.


• Working knowledge of AI/ML, GenAI, RAG, vector databases, and how data platform design enables AI workloads.
  

Roles & Responsibilities

• Lead technical discovery workshops with business, data, analytics, and IT stakeholders to understand target outcomes and constraints.


• Translate business objectives into target-state data architectures, value-driven solution blueprints, and phased transition roadmaps.


• Design end-to-end modern data platforms including ingestion, lakehouse/warehouse, analytics, AI/ML, and GenAI enablement layers.


• Define reference architectures, integration patterns, data models, data quality controls, governance mechanisms, and security architecture.


• Assess legacy data environments and recommend modernization approaches that balance scalability, cost, performance, and delivery practicality.


• Support proposals, RFIs/RFPs, PoCs, architecture diagrams, cost modeling, sizing, and solution defense sessions.


• Partner with cloud, AI, cybersecurity, application, and delivery teams to ensure architectures are secure, scalable, compliant, and delivery-ready.


• Mentor data engineers and junior architects on architecture patterns, engineering standards, and reusable assets.
  

Generic Managerial Skills, If any

• Strong client-facing communication and executive presentation skills.


• Ability to facilitate workshops and align business, IT, enterprise architecture, security, and delivery stakeholders.


• Technical leadership, mentoring, estimation support, solution governance, risk management, and proposal support.


• Ability to balance innovation, implementation feasibility, cost, and commercial viability.
  

Salary Range: $160,000 -$220,000 year

TCS Employee Benefits Summary

Discretionary Annual Incentive.

Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support: Maternal & Parental Leaves.

Insurance Options: Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.

Time Off: Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Qualifications:

BACHELOR OF COMPUTER SCIENCE