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 .