Data Architect

Position Overview :

The Data Architect is responsible for designing, implementing, and managing the data architecture of the organization. This includes ensuring that data is accurate, accessible, secure, and scalable across all systems. The role focuses on developing data models , database solutions , and integration frameworks that support business intelligence, analytics, and digital transformation initiatives.

Key Responsibilities :

Design and implement end-to-end data architecture solutions to support business intelligence, analytics, and data science needs.

Define data standards, governance policies, and data modeling best practices .

Develop conceptual, logical, and physical data models and ensure consistency across systems.

Design and manage data integration processes , including ETL / ELT pipelines.

Collaborate with software engineers, analysts, and stakeholders to understand data needs and translate them into architecture solutions.

Oversee data storage, warehousing, and data lake strategies (on-premises or cloud).

Implement data quality frameworks and metadata management systems .

Ensure data security, privacy, and compliance with regulations (e.g., GDPR, HIPAA).

Work with cloud data platforms such as AWS, Azure, or GCP for scalable data solutions.

Evaluate and recommend new data technologies, tools, and platforms .

Optimize data workflows, queries, and database performance .

Document data flows, architecture diagrams, and system dependencies.

Required Skills & Qualifications :

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field .

Strong expertise in SQL and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra).

Proficiency with data modeling tools (e.g., ERwin, ER / Studio, Lucidchart).

Hands-on experience with ETL / ELT tools (e.g., Informatica, Talend, Apache NiFi, dbt).

Experience with cloud data platforms — AWS (Redshift, Glue), Azure (Synapse, Data Factory), or GCP (BigQuery, Dataflow).

Familiarity with data warehousing and data lake architectures .

Understanding of data governance , master data management (MDM) , and metadata standards .

Knowledge of Python, Spark, or Hadoop ecosystem is a plus.

Excellent problem-solving, analytical, and documentation skills.

Strong communication skills for working with both technical and non-technical stakeholders.

Preferred Qualifications :

Certifications such as :

AWS Certified Data Analytics – Specialty

Google Professional Data Engineer

Microsoft Certified : Azure Data Engineer Associate

DAMA Certified Data Management Professional (CDMP)

Experience implementing modern data architectures (Data Mesh, Data Fabric).

Familiarity with real-time streaming platforms (Kafka, Kinesis).

Experience in AI / ML data pipeline architecture .

Background in enterprise-level data strategy or consulting .