Senior Data Solution Architect

Job description

**Senior Data Solution Architect - Asia Data Office**



Join the Asia Data Office as a Senior Data Solution Architect to lead the design and implementation of scalable, standardized, and reusable data solutions.

This role is ideal for individuals with deep expertise in data modeling and architecture, a passion for reducing technical debt, and the ability to bridge functional teams to deliver cohesive data platforms.

You will also mentor junior staff and supervise contingent workers to ensure best practices are consistently applied.



**Position Responsibilities:**



+ Provide deep expertise in conceptual, logical, and physical data modeling.

Drive architectural decisions that reduce technical debt and increase standardization and reusability across platforms.

+ Act as a bridge between business, engineering, and analytics teams to ensure cohesive and scalable data solutions aligned with strategic goals.

+ Mentor junior engineers and supervise contingent workers, ensuring adherence to best practices in data engineering and architecture.

+ Design and implement enterprise-grade data platforms using modern architecture patterns such as data lakehouse, data mesh, and event-driven systems.

+ Support the development of automated data pipelines and CI/CD practices using tools like dbt, Apache NiFi, and custom frameworks.

+ Architect solutions across cloud platforms (AWS, Azure, GCP) and big data ecosystems (Hadoop, Spark, Hive, Kafka), leveraging services like Databricks, BigQuery, Synapse, and Snowflake.

+ Document architecture designs, metadata management, data lineage, and ensure compliance with data governance and security standards (e.g., GDPR, HIPAA).



**Required Qualifications:**



+ Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related field.

+ 7–10+ years in data architecture, data engineering, or related roles.

+ Experience with agile methodologies and DevOps practices.

+ Proven experience designing and implementing enterprise-scale data platforms.

+ Data Modeling: Conceptual, logical, physical models; normalization/denormalization.

+ Database Technologies: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra), Graph DBs (Neo4j).

+ ETL/ELT Tools: Informatica, Talend, dbt, Apache NiFi, custom pipelines.

+ Big Data Ecosystem: Hadoop, Spark, Hive, Kafka.

+ Cloud Platforms: AWS, Azure, GCP – Databricks, BigQuery, Synapse, Snowflake.

+ Programming: Python, Scala, Java, or similar for data engineering tasks.

+ Architecture Patterns: Data lakehouse, data mesh, event-driven architecture, microservices.

+ Strong understanding of business strategy and how data supports it.

+ Excellent communication and stakeholder management skills.

+ Ability to mentor junior engineers and collaborate across cross-functional teams.



**Preferred Qualifications:**



+ Cloud: AWS Certified Data Analytics, Azure Data Engineer, Google Cloud Professional Data Engineer

+ Data Management: CDMP (Certified Data Management Professional)

+ Architecture: TOGAF, DAMA-DMBOK

+ Data Governance & Security: Metadata management, data lineage, access control, compliance (GDPR, HIPAA)



**_When you join our team:_**



+ We’ll empower you to learn and grow the career you want.

+ We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.

+ As part of our global team, we’ll support you in shaping the future you want to see.



**Acerca de Manulife y John Hancock**



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**Modalidades de Trabajo**



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