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Data Architect

CBOT · Istanbul

Senior 🇬🇧 English
SQL Microsoft Azure Google Cloud Platform AWS ETL/ELT Apache Spark Databricks

Job description

About the role

We are seeking an experienced Data Architect to design, govern, and evolve our enterprise cloud data architecture across OTT, CRM, ISP, and analytics platforms. You will work closely with business stakeholders, data engineers, analytics teams, and software developers to deliver scalable, secure, and high‑performance data solutions.

Key responsibilities

  • Design and maintain enterprise data architecture, including conceptual, logical, and physical models.
  • Define and implement cloud‑native data warehouse, data lake, and lakehouse solutions.
  • Establish data integration standards for internal and external systems.
  • Architect data ingestion, ETL/ELT, streaming, and batch processing pipelines.
  • Implement data governance, metadata management, master data management, and data quality frameworks.
  • Ensure data consistency, integrity, lineage, and traceability across platforms.
  • Define API, data service, and real‑time integration standards.
  • Design secure data architectures compliant with GDPR and regional privacy regulations.
  • Optimize storage, partitioning, indexing, and query performance for large analytical workloads.
  • Evaluate and recommend new cloud technologies and architectural best practices.
  • Provide technical leadership, conduct architecture reviews, and mentor engineering teams.

Required profile

  • Bachelor’s degree in Computer Science, Information Systems, Engineering or a related field.
  • Minimum 7 years of experience in data engineering, data warehousing, or enterprise data architecture.
  • At least 3 years of hands‑on experience in data or solution architecture roles.
  • Strong knowledge of enterprise data architecture methodologies and modeling techniques (dimensional, Data Vault, normalized).

Required skills

  • SQL with query performance optimization.
  • Cloud platforms: Microsoft Azure, Google Cloud Platform, or AWS.
  • ETL/ELT design and modern data integration patterns.
  • Big data technologies such as Apache Spark and Databricks.
  • Data governance, metadata management, master data management (MDM) concepts.

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Published 1 ay önce

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CBOT

Istanbul