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
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