Data Architect

3 weeks ago


Delhi, India Landmark Group Full time
We are seeking a highly skilled
Data Architect
to design, optimize, and manage our enterprise data architecture. The role involves defining how data is collected, stored, accessed, and leveraged across the organization, ensuring scalability, security, and performance. You will collaborate with stakeholders, engineers, and analysts to establish robust data models and frameworks that drive business intelligence and advanced analytics.
Key Responsibilities
Design, implement, and maintain the
overall data architecture
(data models, standards, and guidelines).
Develop and optimize
data pipelines, ETL/ELT processes , and integration frameworks for structured and unstructured data.
Define and enforce
data governance, security, and compliance
policies (GDPR, HIPAA, etc. as applicable).
Collaborate with data engineers, BI developers, and analysts to ensure data availability and usability.
Evaluate and recommend
data storage solutions
(data lakes, data warehouses, cloud platforms).
Define
metadata management, master data management (MDM), and data lineage
strategies.
Establish performance tuning and cost optimization practices for large-scale data environments.
Provide technical leadership in
cloud data platforms
(AWS, Azure, GCP) and emerging technologies.
Translate
business requirements into scalable data solutions
that support analytics, AI/ML, and reporting.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
Proven experience (9+ years) as a
Data Architect, Data Engineer, or Database Architect .
Strong knowledge of
data modeling (conceptual, logical, physical)
and database design.
Expertise in
SQL/NoSQL databases
(e.g., Oracle, MySQL, PostgreSQL, MongoDB, Cassandra).
Hands-on experience with
data integration tools
(Informatica, Talend, Apache Nifi, dbt).
Proficiency with
cloud data platforms
(AWS Redshift, Azure Synapse, GCP BigQuery, Snowflake).
Familiarity with
big data frameworks
(Hadoop, Spark, Kafka) and
real-time streaming data .
Strong understanding of
data security, compliance, and governance frameworks .
Excellent communication and stakeholder management skills.
Preferred Qualifications
Experience with
containerization & orchestration
(Docker, Kubernetes).
Knowledge of
AI/ML pipelines
and data science workflows.
Certifications in cloud platforms (AWS Certified Data Analytics, Google Professional Data Engineer, Azure Data Engineer Associate).
Experience in designing
data mesh / data fabric architectures .

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