Enterprise Data Architect
Enterprise Data Architect – Job
Description
Location: Bangalore
Experience:
15+ years in Data Engineering & Data Platforms
Employment Type: Full-time
About Aptus Data Labs
Aptus Data Labs is a global Data
Engineering and AI solutions partner helping enterprises build modern,
scalable, and intelligence-driven organizations. With deep expertise across
cloud platforms, advanced analytics, AI/ML, and enterprise data transformation,
we empower businesses to unlock the full value of their data. Our focus on
innovation, domain excellence, and engineering quality enables us to deliver
high-impact platforms—ranging from enterprise data lakes to AI-driven
automation and industry-specific solutions. Trusted by leading companies across
the US, India, Africa, and Europe, Aptus Data Labs is committed to shaping
future-ready digital ecosystems that drive growth, efficiency, and strategic
advantage.
About the Role
We are seeking a highly accomplished
Enterprise Data Architect with deep expertise in designing modern data
platforms, integrating complex enterprise datasets, and driving large-scale
digital and AI initiatives. The ideal candidate brings 15+ years of strong
experience in data engineering, data platforms, data governance, data
integration, and data operations, with 5+ years of hands-on Databricks
Lakehouse implementation on AWS and strong Reltio MDM experience.
This role is instrumental in shaping the
enterprise data foundation, leading multi-domain integrations, and enabling
AI-ready architectures across global teams in the US, India, and Ireland.
Key Responsibilities
1. Lead the enterprise data
architecture strategy, focusing on scalability, modernization,
interoperability, and business alignment.
2. Architect and operationalize
Databricks Lakehouse solutions on AWS, including ingestion, transformation,
orchestration, governance, and consumption layers.
3. Design and implement Medallion
architecture (Bronze–Silver–Gold) with 100+ source integrations using Boomi
Integrator and Databricks pipelines.
4. Drive enterprise Master Data
Management (MDM) using Reltio, including entity modeling, data quality,
match-merge rules, survivorship, workflows, and golden record stewardship.
5. Establish frameworks for
metadata management, data quality, lineage, cataloging, and governance,
leveraging Unity Catalog and AWS-native security.
6. Enable AI and analytics teams
by building AI-ready datasets, feature stores, and GenAI-supporting data
pipelines.
7. Provide leadership, mentorship,
and architectural oversight for data engineering, governance, and platform
teams.
8. Implement enterprise standards
for data security, IAM, compliance (GDPR/HIPAA), observability, and cloud cost
optimization.
9. Collaborate with global
business stakeholders across the US, India, and Ireland to drive data
modernization, cloud migration, and aligned domain strategies.
Requirements
Required Skills & Experience
- 15+ years of hands-on
experience in data engineering, data platforms, data integration, data
governance, and data operations.
- Strong hands-on experience with Reltio MDM, including configuration, hierarchy management, entity
modeling, match/merge, and golden record creation.
- 5+ years of solid expertise in Databricks Lakehouse (Delta Lake,
PySpark, Unity Catalog, MLflow, and Databricks AI).
- Proven expertise in AWS data ecosystem: S3, Glue, EMR, Lambda,
Athena, Redshift, Lake Formation, IAM.
- Strong experience in implementing
Medallion architecture across 100+ data sources using:
- Boomi Integrator
- Databricks pipelines (batch and streaming) - Advanced proficiency in SQL,
Python, PySpark, and API-driven integrations.
- Deep understanding of data governance, metadata, lineage,
observability, and MDM frameworks.
- Experience with modern data
stack tools (Snowflake, dbt, Airflow, Kafka) is an advantage.
- Excellent communication skills,
both verbal and written, with the ability to collaborate effectively with teams
across the US, India, and Ireland.
- AWS or Databricks
certifications preferred.
Education
Bachelor’s or Master’s degree in Computer
Science, Information Systems, Data Engineering, or a related field.