AWS Data Architect

Golden Opportunities; Bengaluru; Remote; INR 4,000,000 - 6,400,000; Full time

Job summary

Golden Opportunities seeks a senior data engineering/analytics architect with 7+ years of experience across data platforms and AWS analytics. You will own the reporting-layer data architecture, ensure semantic models align with business needs, and guide production BI platforms with a focus on data governance and security.

The role demands strong communication skills, leadership across engineers, and the ability to handle service requests, dashboards, and production defects with strict SLAs.

Qualifications

• 7+ years in data engineering or analytics architecture, with substantial hands-on AWS-based analytics.
• Experience owning the reporting-layer data architecture and semantic model and turning business requirements and support tickets into robust data models.
• Experience running enterprise BI platforms in production/support capacity with SLA-driven operations.
• Experience setting data-modelling, security and performance standards, and providing technical leadership to engineers and architects.
• Understanding of incident, service-request, problems, and change management processes for analytics and reporting services.
• Ability to manage dashboard enhancements, access requests, refresh failures, data-quality issues, production defects, and user queries within agreed service levels.
• Strong knowledge of data governance, data quality, metadata, KPI governance, access controls, and business glossary management.
• Experience with Jira, Confluence, ServiceNow, or similar delivery and support-management tools.

Responsibilities

• Own the reporting-layer data architecture and semantic model from business requirements to robust data models.
• Manage enterprise BI platforms in production and support capacity (BAU/L2-L3) with SLA adherence.
• Set data modelling, security, and performance standards and provide technical leadership.
• Oversee incident, service requests, problems, and changes for analytics services.
• Coordinate dashboard enhancements, access requests, and data-quality issues within SLAs.
• Maintain data lineage, quality, metadata, KPI governance, access controls, and glossary management.

Skills

AWS analytics

SQL proficiency

Data modelling

Data governance

Data lineage

Data quality

BI platforms

Security design

Semantic layer

Redshift

Data mesh

Data product

Communication

Education

Graduation

Tools

Jira

Confluence

ServiceNow

AWS Console

Job description

Candidate Specification

7+ years overall, Relevant 7+ years
Candidate Location: Pan India

Education and Certification

Any Graduation

Job description

• 7+ in data engineering or analytics architecture, with substantial hands-on AWS-based analytics.
• Experience owning the reporting-layer data architecture and semantic model and turning business requirements and support tickets into robust data models.
• Experience running enterprise BI platforms in a live production / support capacity (BAU / L2-L3, SLA-driven).
• Experience setting data-modelling, security and performance standards, and providing technical leadership to engineers and architects.
• Understanding of incident, service-request, problems, and change management processes for analytics and reporting services.
• Ability to manage dashboard enhancements, access requests, refresh failures, data-quality issues, production defects, and user queries within agreed service levels.
• Strong knowledge of data lineage, data quality, metadata, KPI governance, access controls, and business glossary management.
• Experience with Jira, Confluence, ServiceNow, or similar delivery and support-management tools.

Key technical skills

• AWS analytics stack Glue, Lake Formation, Athena and S3. Amazon QuickSight datasets, SPICE and the semantic layer.
• Exposure to strong SQL and data modelling.
• Row-/column-level security design, and performance / cost tuning.
• Amazon Bedrock / natural-language analytics.
• Experience with Redshift or other cloud data warehouses.
• Exposure to data-mesh / data-product patterns.
• Financial-services data domain exposure.
• Superior communication skills written and oral.