Job Title: Data Architect

Experience: 10+ years

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Key Responsibilities:

- Data Leadership: Define and drive the data architecture and AI strategy aligned with the organization's goals, emphasizing data-driven decision-making and enhancing operational efficiency.
- Architecture Design: Lead the design and deployment of scalable, efficient data architectures that support advanced analytics, reporting, and machine learning applications.
- Integration Solutions: Oversee the development of integration strategies to ensure seamless data flow between various IT systems and analytics platforms.
- Data Governance & Compliance: Implement and enforce data governance frameworks, ensuring compliance with regulatory standards such as FedRAMP and HITRUST, and promoting data integrity, security, and quality.
- Collaboration with Stakeholders: Work closely with enterprise architects, data scientists, analysts, and IT teams to understand data requirements, provide architectural guidance, and ensure successful project execution.
- Emerging Technology Assessment: Assess and recommend new technologies that can enhance data architecture and analytics, particularly in healthcare applications.
- Documentation and Standards: Develop comprehensive documentation for data architecture standards, best practices, and processes to be followed by internal teams.
- Mentorship and Team Development: Mentor and guide data architects and engineers, fostering a culture of continuous learning and innovation within the data team.

Experience:

- 10+ years of experience in data architecture roles.

Technical Skills:

- Expertise in data engineering frameworks and tools such as Apache Spark, Apache Kafka, and Airflow.
- Deep understanding of relational, NoSQL, and vector databases,



including SQL Server, Oracle, Teradata, PostgreSQL, MongoDB, Cassandra, SingleStore, and Pinecone.
- Proficiency in data warehousing solutions like Snowflake, Amazon Redshift, Google BigQuery, and Databricks.
- Strong experience with ETL processes and tools such as Apache NiFi, Talend, Informatica, and Mulesoft.
- Familiarity with microservices architecture and tools like BFF, Spring, JDK, MERN, or MEAN stack is a plus.
- Knowledge of healthcare data interoperability frameworks like HL7 V2, HL7 V3, FHIR, and SNOMED is a plus.
- Experience with machine learning frameworks (e.g., Python, Keras, TensorFlow) and Generative AI, Large Language Models, and retrieval-augmented generation solutions (e.g., GPT, Llama2, Claude 2) is advantageous.
- Familiarity with big data technologies such as Hadoop and Spark is a plus.

Collaboration Skills:

- Proven ability to work with cross-functional teams, driving data initiatives from design to execution.

Responsible Use of AI:

- Familiarity with data privacy and ethical considerations surrounding AI implementations.

Analytical Mindset:

- Robust analytical and problem-solving abilities, with a focus on generating actionable insights from complex datasets.

Communication Skills:

- Excellent verbal and written communication skills, with the ability to convey complex data concepts to both technical and non-technical stakeholders.

Qualifications:

- Bachelor's degree in Computer Science, Engineering, or related fields (Master's degree preferred).
- Advanced certifications in architecture, such as TOGAF or cloud-specific certifications (AWS/Azure/GCP Solutions Architect).
- Advanced certifications in data management, including CDMP, Cloud Data Architect, and Snowflake Architect certifications.

📌 Data Architect (Bengaluru)
🏢 NR Consulting
📍 Bengaluru