Are you passionate about building enterprise-scale data platforms that power advanced analytics, AI, and business transformation?
We are seeking a highly experienced Data Engineering Architect to lead the design and implementation of modern, scalable, and secure data ecosystems. This role offers an opportunity to shape the organization’s data strategy while driving innovation across Cloud, Big Data, Real-Time Analytics, Data Governance, and AI‑ready architectures.
If you thrive in solving complex data challenges and enjoy influencing enterprise-wide technology decisions, we’d love to hear from you.
About the Role
As a Data Engineering Architect, you will be responsible for designing and governing end-to-end data architectures that support business intelligence, advanced analytics, machine learning, and AI initiatives.
You will work closely with business leaders, data scientists, architects, and engineering teams to build scalable data solutions that transform raw data into actionable insights.
Responsibilities
- Define and implement enterprise-wide data architecture and engineering strategies
- Design scalable, secure, and high-performance data platforms across cloud and hybrid environments
- Build modern data ecosystems that support analytics, reporting, AI, and machine learning workloads
- Design, develop, and optimize batch and real-time data pipelines
- Build robust ETL/ELT frameworks for data ingestion, transformation, and processing
- Integrate structured, semi‑structured, and unstructured data from multiple enterprise sources
- Architect scalable data lake, data warehouse, and lakehouse solutions
- Ensure data reliability, quality, governance, and security across platforms
Cloud & Big Data Solutions
- Lead cloud‑native data platform implementations across AWS, Azure, and GCP
- Spark
- Hadoop
- Kafka
- Kinesis
- Streaming Technologies
AI & Advanced Data Enablement
- Build AI‑ready data foundations supporting predictive analytics and machine learning initiatives
- Work with Graph Databases and Vector Databases to enable next‑generation AI and knowledge‑driven applications
- Collaborate with Data Science and AI teams to accelerate enterprise AI adoption
Leadership & Governance
- Drive best practices in Data Engineering, Data Governance, Security, and DevOps
- Lead architecture reviews, technology evaluations, and strategic initiatives
- Mentor engineering teams and influence enterprise data standards
- Partner with stakeholders to translate business requirements into scalable technical solutions
What We’re Looking For
Core Experience
- 15+ years of experience in Data Engineering, Data Architecture, or Enterprise Data Management
- Proven track record of designing and implementing large‑scale enterprise data platforms
- Strong leadership, stakeholder management, and solution architecture experience
Technical Expertise
Programming
- Python
- Java
- Spark
- ETL / ELT Frameworks
- Data Lakes
- Data Warehouses
Databases
- SQL & NoSQL
- Redshift
- DynamoDB
- MongoDB
- Synapse
- BigQuery
- RDS
- AWS
- GCP
- Hadoop
- Kafka
- Kinesis
Data Warehousing
- Snowflake
- Redshift
- BigQuery
DevOps & Automation
- CI/CD
- Docker
- Infrastructure Automation
APIs & Integration
- REST APIs
- Messaging Platforms
Graph Databases
- Amazon Neptune
- RDF4J
- Neo4j
Vector Databases
- Pinecone
- FAISS
Experience with
- Informatica
- Talend
- dbt
Exposure to
- NLP Solutions
- AI/ML Platforms
- Customer Segmentation & Advanced Analytics
- Banking
- Insurance
- Mortgage
Shape the future of cloud, analytics, and AI architecture
Work on cutting‑edge technologies including Big Data, Real-Time Analytics, Graph Databases, and AI‑ready platforms
Collaborate with senior technology leaders and business stakeholders
Influence strategic technology decisions across the organization
Build platforms that power data-driven innovation at scale
If you’re passionate about Data Engineering, Cloud Architecture, Big Data, Analytics, and AI-driven innovation, we’d love to connect with you.
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