Job Details

The Senior Data / Information Architect will lead the design and implementation of enterprise data architecture solutions for key strategic initiatives. As the chief SME architect, you will leverage your extensive expertise in data architecture, governance, integration, and analytics to deliver hands-on solutions that align with business outcomes. This role requires a combination of technical expertise, strategic thinking, and leadership skills to guide data and BI analytics initiatives, ensuring data strategies are aligned with business goals and that PSS data is accessible, secure, and valuable across the organization. You will also play a pivotal role in advancing the organization's modernization journey in alignment with the Enterprise data strategy. A key to success in this role is a unique blend of data management skills, business knowledge, and the ability to work with and influence multiple cross-functional teams within IT and business to identify the right solutions.

Accountabilities include:

1. Architecture and design reviews: Lead the design and implementation of end-to-end scalable, secure, and efficient data/information architectures across the PSS Data LOB. Play a key leadership role in architecture design reviews, identifying gaps and recommending design changes. Actively lead and participate in the architecture community to drive modernization opportunities for the advancement of PBM technology while considering the complexities of our IT landscape. Develop strategies for data storage, integration, and retrieval across structured and unstructured data systems. Establish data models and architecture that support data lakes, data warehouses, and cloud-based systems. Drive architecture reviews, identify gaps and recommend design improvements.
2. Data Integration & Management: Design solutions that enable the seamless data flow between source systems, applications, and cloud platforms. Guide data lifecycle management, from data collection, processing, storage, archival, and disposal. Develop real-time and batch processing solutions that enable effective analytics and reporting. Foster data integration and interoperability, enabling seamless data sharing by solving complex data integration problems using optimal ETL/ELT patterns, frameworks, and query techniques.
3. Business Intelligence and Analytics: Collaborate with data engineering, BI, analytics, and data science teams to ensure data architecture supports business needs. Lead the development of data models and architectures that empower business users to derive actionable insights.
4. Reference architecture and implementation: Provide leadership in assembling reference architectures to support cloud migration and cloud-native applications. Develop and maintain architecture design documents, roadmaps design patterns, and use-case driven designs.
5. Leadership and Innovation: Provide oversight from project inception to delivery, guiding data engineers, BI engineers, data modelers, and architects. Stay updated on industry trends and emerging technologies in data/information architecture, cloud computing, big data, analytics, and AI.
6. Technology Evaluation and Selection: Lead build vs buy analysis and recommend tools and technologies based on qualitative and quantitative evaluations. Oversee proofs-of-concept and deep-dives into partner technologies.
7. Collaboration & Stakeholder Engagement: Work with business leaders, data stewards, security, digital, and engineering teams to ensure alignment with business objectives. Mentor and coach data engineers and architects and contribute to data governance, ensuring data integrity, quality, security, and compliance.
8. Security and Compliance: Ensure data/information architectures meet security, privacy, and regulatory requirements. Implement robust data security frameworks, including encryption, data masking, and access controls.
9. Cost optimization identification: Collaborate with stakeholders to identify opportunities to reduce costs through simplification, configurability, and reduction of.

Growth: Opportunity to expand towards leadership role as relevant and appropriate, performance and skill-based opportunity.

Required Qualifications:

1. 10+ years of experience in designing, developing, and managing large-scale data architectures, including data lakes, data warehouses, and cloud environments (Azure, preferably Google Cloud).
2. 8+ years of experience in cloud native-data architectures, data integration, API-based data integration, ELT/ETL, batch, and real-time data processing.
3. Expertise in cloud design and architecture (Azure, AWS, preferably GCP) to deliver large-scale distributed solutions.
4. Strong business acumen with the ability to align data/information architecture strategies with business objectives.
5. Proven leadership in cross-functional teams and fostering a data-driven culture.
6. Extensive knowledge of data modeling, data governance, database design, data warehousing, ETL/ELT processes, and data technologies (e.g., Spark, relational and NoSQL databases).
7. Proficiency with data architecture tools and platforms (e.g., ERwin, Kafka, Redis) and familiarity with cloud data services (e.g., AWS, Azure, Google Cloud).
8. 8+ years of experience in Python and modern data platforms like BigQuery, Redshift, Spark, Cloud SQL, DataProc, Cloud Storage & Dataflow/Data Fusion.
9. 8+ years of experience in SQL/NoSQL databases, cloud databases, and data streaming technologies (Kafka).
10. 8+ years of experience in orchestration tools (Airflow, Cloud Composer) and experience in CI/CD pipelines, automation, and DevOps practices.

Preferred Qualifications:

1. In-depth knowledge of data management, data governance frameworks, data cataloging, and master data management.
2. Hands-on coding experience in data integration technologies (on-prem & cloud) and modern technology stacks (Cloud, DevOps, Kafka, etc.)
3. In-depth experience with security frameworks, including encryption, access controls, and compliance with regulatory requirements. Skilled in enterprise tools (DevSecOps, DataOps), agile methodologies, and product-driven approaches for rapid development and iteration of data architectures to meet evolving business needs. Familiar with data frameworks such as Data Fabric, Data Mesh, Data Lakehouse, Lambda architectures.
4. Strong problem-solving abilities to complex data and analytics challenges.
5. Proven experience in driving adoption of cloud-native/cloud-first architectures.
6. Excellent communication skills, engaging both technical and non-technical stakeholders.
7. Strong Knowledge in BI Tools MicroStrategy, Tableau, Thoughtspot, and PowerBI.
8. Proven leadership in data modernization or digital transformation initiatives. Experience in regulated industries with compliance requirements. Healthcare/PBM industry experience strongly preferred.

Soft Skills:

1. Ability to teach and upskill talent within the organization.
2. Thought leadership and mentoring.
3. Deep collaboration skills: Ability to work as a team player, seeking alignment and able to influence business outcomes.

Education:

1. Bachelor's degree in computer science or related field.
2. Master's degree in computer science or related preferred.