Lifesciences Domain Consultant

Experience: 10–15+ years (suggested) Role: Senior Data Architect Employment Type: Full-time Location: As per client requirement

We are looking for an experienced Senior Data Architect to design, develop, and govern scalable, secure, and high-performance enterprise data architectures. The ideal candidate will have strong expertise in cloud data platforms, data modeling, data engineering, data governance, and modern data architecture patterns.

• Design and implement enterprise-wide data architecture, including data lakes, data warehouses, and lakehouse solutions.
• Define data architecture standards, data models, integration patterns, and technology roadmaps.
• Architect scalable data pipelines for batch and real-time data processing.
• Design and optimize ETL/ELT workflows and data integration solutions.
• Lead cloud data architecture initiatives across AWS, Azure, or Google Cloud.
• Implement data governance, data quality, metadata management, lineage, and security frameworks.
• Collaborate with business stakeholders, data engineers, analytics teams, and solution architects.
• Evaluate data technologies and recommend solutions based on scalability, performance, cost, and business needs.
• Ensure compliance with enterprise security policies and applicable data privacy regulations.
• Provide technical leadership, conduct architecture reviews, and mentor data engineering teams.

• Strong experience in enterprise data architecture and data platform design.
• Expertise in data modeling: conceptual, logical, and physical data models.
• Hands-on knowledge of SQL, relational databases, and NoSQL databases.
• Experience with ETL/ELT tools and data integration frameworks.
• Strong understanding of data lakes, data warehouses, and lakehouse architecture.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of distributed data processing technologies such as Apache Spark, Kafka, or Hadoop.
• Experience with data governance, data quality, metadata, and master data management.
• Strong stakeholder management and technical leadership skills.

• Experience with Snowflake, Databricks, BigQuery, or Amazon Redshift.
• Knowledge of dbt, Airflow, Azure Data Factory, or Informatica.
• Experience designing real-time streaming and event-driven data architectures.
• Familiarity with data mesh, data fabric, and modern cloud-native architecture patterns.
• Exposure to AI/ML data platforms and GenAI data requirements.

Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related discipline.

• Enterprise data architecture and technology roadmap.
• Scalable, secure, and cost-effective data platforms.
• Standardized data models and integration frameworks.
• Improved data quality, governance, and accessibility.
• Technical guidance for data engineering and analytics teams.