Data Architect

Randstad Türkiye; Fatih; On-site; TRY 300,000 - 600,000; Full time

Job summary

Randstad Türkiye is seeking a Data Architect to centralize data architecture, migrate dispersed data, and build an AI/ML-ready data platform. You will establish a unified data framework and lead secure, governance-driven data sharing across multiple systems.

You will also ensure KVKK/GDPR compliance, design robust data governance, and collaborate with engineering, analytics, and business units to deliver scalable data solutions in a fast-paced environment.

Qualifications

• In-depth knowledge of data architecture, governance, and strategy.
• End-to-end involvement in Data Warehouse projects and modern data transitions.
• Designs conceptual, logical, and physical data models for structured and unstructured data.
• Experience with hybrid-cloud architectures and big data services.

Responsibilities

• Centralize data architecture and migrate scattered data into a centralized, AI/ML-ready structure.
• Establish “Single Source of Truth” standards for cross-system data sharing.
• Design secure data sharing protocols and prevent duplicates across systems.
• Define and implement data governance rules with ongoing auditing and compliance.
• Ensure KVKK/GDPR compliance and adapt architecture to regulatory changes.
• Bridge technical teams and business stakeholders with fluent cross-functional communication.

Skills

Domain expertise

Data governance

Data modeling

Modern data stack

Data security & privacy

Communication

Leadership

Continuous learning

Industry experience

English proficiency

Education

Bachelor’s degree in Engineering

Tools

Snowflake

Databricks

AWS

Azure

GCP

ETL/ELT orchestration

Job description

We are looking for an 'Data Architect' for our client.

Responsibilities include:

• Centralizing Data Architecture: Migrating scattered data from various systems into a centralized structure, building an optimized and enriching data architecture tailored for Artificial Intelligence (AI) and Machine Learning (ML) processes.
• Single Source of Truth: Establishing "Single Source of Truth" standards for cross-system data sharing; ensuring that customers are represented uniformly and consistently across all systems, regardless of their acquisition channel.
• Data Integrity Security: Designing secure data sharing protocols, as well as creating and deploying systemic rules to prevent data duplication.
• Data Governance: Defining Data Governance rules, guiding technical teams in their implementation, and ensuring continuous auditing and compliance.
• Regulatory Compliance: Designing a data architecture that is 100% compliant with legal frameworks and audit standards such as KVKK (Turkish Personal Data Protection Law) and GDPR; agilely adapting the architecture to any regulatory changes.
• Cross-Functional Liaison: Acting as a bridge between highly technical software/infrastructure teams and business end-users, serving as a guide who fluently speaks and translates the language of both sides.

Qualifications

• Domain Expertise: In-depth knowledge and profound experience in data architecture, data governance, and data strategy development.
• Project Experience: Active, end-to-end involvement in Data Warehouse projects and the transition from traditional to modern data structures.
• Data Modeling Mastery: Expertise in designing conceptual, logical, and physical data models for both structured (Relational/ERP) and unstructured (NoSQL/Lakehouse) datasets.
• Modern Data Stack Strategy: Proficiency in designing hybrid-cloud data platforms (Snowflake, Databricks, or cloud-native AWS/Azure/GCP big data services) and ETL/ELT orchestration.
• Data Governance Quality: Ability to implement enterprise-grade data governance frameworks (Data Cataloging, Lineage, Master Data Management) to ensure compliance with KVKK, GDPR, and holding-level audit requirements.
• Security Privacy: Expert-level knowledge in data security, data privacy, and the technical integration of KVKK and GDPR regulations into the infrastructure.
• Communication Technical Acumen: Possessing the high technical proficiency required to debate solutions with technical authorities, combined with the strong communication skills needed to guide and influence business units.
• Leadership: A visionary with strong leadership qualities who doesn't just set the rules, but actively persuades stakeholders to ensure their successful implementation.
• Continuous Learning: Always open to learning new technologies, tools, and architectural approaches.
• Industry Experience: Preferably experienced in working with complex data structures within the Manufacturing (sector experience is a significant plus), Retail, or Telecommunications industries.
• Education: Bachelor’s degree from an Engineering faculty.
• Language Skills: Advanced level of both spoken and written English.