Data Architect

At Citius Tech, we constantly strive to solve the industry's greatest challenges with technology, creativity, and agility. With over 8,500 healthcare technology professionals worldwide, Citius Tech powers healthcare digital innovation, business transformation, and industry-wide convergence for over 140 organizations through next-generation technologies, solutions, and products. We aim to accelerate the transition to a human-first, sustainable, and digital healthcare ecosystem with the world's leading Healthcare and life sciences organizations and our partners.

Our vision:

To inspire new possibilities for the health ecosystem with technology and human ingenuity.

Role:
Data Architect

Role

Summary:

• We are seeking an experienced Data Architect to define and evolve enterprise data architecture and design scalable, secure, high-performing data solutions aligned with business strategy. The role will shape target-state architecture, platform capabilities, data patterns, and modernization roadmaps across ingestion, storage, transformation, governance, analytics, and AI consumption.
• The ideal candidate combines deep architecture expertise with strong understanding of Finance, Sales, or Operations. This role partners with Product, Engineering, Analytics, AI, and business leaders to establish architecture direction, guide solution design, and ensure the data platform remains reusable, interoperable, governed, and future‑ready.

Key Responsibilities:

Design Scalable Data Solutions:

• Architect end-to-end data solutions spanning ingestion, integration, transformation, storage, serving, analytics, and AI consumption.
• Define conceptual, logical, and physical data architectures and select appropriate patterns for batch, streaming, and near-real-time use cases.
• Ensure designs meet scalability, performance, resilience, availability, security, and disaster-recovery requirements.
• Lead architecture reviews and guide engineering teams through solution implementation.

Build and Evolve the Data Platform:

• Define target-state architecture for modern data warehouses, lake houses, data lakes, and analytical platforms.
• Create platform blueprints, reference architectures, reusable patterns, and technology standards.
• Guide legacy modernization and migration to cloud-native, Snowflake-aligned architectures.
• Evaluate platform capabilities and recommend investments based on business value, interoperability, scalability, and cost.

Drive Data Strategy and

Collaboration:

• Translate business strategy into data capabilities, architecture roadmaps, and prioritized modernization initiatives.
• Partner with Product, Engineering, Analytics, AI, Security, and business leaders on architecture decisions.
• Communicate trade-offs, risks, dependencies, and recommendations to technical and executive stakeholders.
• Provide architecture leadership and mentor teams on patterns and design decisions.

Ensure Standards and Innovation:

• Establish standards for data modeling, integration, metadata, lineage, quality, interoperability, security, and responsible data use.
• Ensure solution designs align with enterprise architecture, privacy, compliance, and governance principles.
• Evaluate emerging technologies in AI, automation, streaming, and cloud data platforms.
• Promote reusable data products, engineering excellence, and continuous architecture improvement.

Mandatory

Skills:

• Enterprise and solution data architecture
• Snowflake-aligned platform architecture
• Conceptual, logical, and physical data modeling
• Data warehouse, lakehouse, and data-lake architecture
• Batch, streaming, real-time, API, and event-driven integration patterns
• Cloud architecture on Azure, AWS, or GCP
• Metadata, lineage, data-quality, privacy, and governance architecture
• Performance, resilience, availability, disaster recovery, and cost optimization
• Architecture standards, reference patterns, design reviews, and technology evaluation

Functional / Domain

Experience:

Experience in at least one of the following domains:

• Finance — FP&A, revenue analysis, budgeting, forecasting, or P&L analytics
• Sales — sales operations, pipeline analytics, CRM insights, or revenue growth
• Operations — process optimization, workforce planning, productivity, or…