ERM International - Data Architect

Description :

Job Summary :

We are seeking an experienced Data Architect to join our Technology team and play a key role in driving enterprise-wide data strategy, architecture, and governance initiatives. The ideal candidate should possess strong expertise in data architecture, analytics, data engineering, cloud platforms, and modern data management practices.

In this role, you will collaborate closely with business stakeholders, architects, engineers, product teams, and data scientists to design scalable, secure, and business-aligned data ecosystems that support analytics, reporting, governance, and digital transformation initiatives.

Key Responsibilities :

Enterprise Data Architecture :

- Define and drive enterprise-wide data and information management architecture aligned with business and technology strategy.

- Design scalable and sustainable data architectures supporting operational, analytical, and reporting workloads.

- Develop enterprise data models, data flow architectures, and integration frameworks across structured and unstructured data environments.

- Establish standards, principles, and best practices for enterprise data management and governance.

Data Engineering & Analytics Enablement :

- Lead end-to-end architecture for data-intensive and analytics-driven projects involving :

1. Data acquisition

2. Ingestion

3. Integration

4. Transformation

5. Storage

6. Consumption

7. Design modern data platforms supporting BI, analytics, AI/ML, and reporting initiatives.

8. Provide architectural guidance for implementing scalable data engineering and analytics solutions.

Cloud & Modern Data Platforms :

- Architect and support cloud-based data solutions leveraging Azure and AWS data services.

- Design and optimize cloud-native data lakes, warehouses, and distributed data processing platforms.

- Evaluate emerging technologies, big data architectures, and modern data processing frameworks.

Data Governance & Quality :

- Establish and promote data governance, ownership, lineage, quality, and lifecycle management practices.

- Ensure enterprise data platforms comply with corporate, regulatory, and reporting requirements.

- Define governance models for data in motion and data at rest across enterprise systems.

- Collaborate with stakeholders to improve data consistency, trustworthiness, and accessibility.

Stakeholder Collaboration & Technical Leadership :

- Work closely with product owners, engineers, business teams, and data scientists to understand evolving business and data requirements.

- Provide technical leadership and architectural direction across enterprise data initiatives.

- Mentor engineering teams and contribute to building a strong enterprise data community.

- Drive innovation and continuous improvement across data platforms and practices.

Agile & Engineering Practices :

- Support Agile delivery methodologies and modern engineering practices.

- Promote test-driven development, automated testing, CI/CD, and source control best practices within data engineering teams.

- Participate in architecture reviews, technical governance, and strategic planning discussions.

Required Skills & Experience :

- 8 to 12 years of experience in Data Architecture, Data Engineering, or Enterprise Data Management.

- Proven experience as an Enterprise Data Architect designing large-scale data ecosystems.

- Strong experience in end-to-end implementation of analytics and data-intensive projects.

- Expertise in data acquisition, ingestion, integration, transformation, and data consumption frameworks.

- Strong understanding of data governance, data quality, metadata management, and lineage concepts.

- Hands-on experience with Azure and AWS cloud data services.

- Experience with modern data modelling techniques including conceptual, logical, and physical data modelling.

- Knowledge of big data architectures, distributed processing, and modern analytics platforms.

- Strong understanding of Agile methodologies, automated testing, and source control practices.

- Excellent stakeholder management, communication, and problem-solving skills.

Preferred Qualifications :

- Experience with modern data platforms such as Snowflake, Databricks, Redshift, Synapse, or BigQuery.

- Knowledge of ETL/ELT tools and orchestration platforms.

- Exposure to AI/ML data platforms and advanced analytics ecosystems.

- Familiarity with DataOps and MLOps practices.

- Cloud certifications in Azure or AWS are preferred.

- TOGAF or enterprise architecture certifications are an added advantage.