The role
Job description
We are looking for an experienced Data Architect with strong expertise in Snowflake , modern cloud data platforms, and Business Intelligence (BI). The ideal candidate will own end-to-end data architecture, design scalable data engineering and analytics solutions, and translate complex business requirements into reliable, high-performance data platforms.
The role requires a combination of hands-on technical architecture, BI and semantic modeling expertise, stakeholder management, and technical leadership.
Key Responsibilities
1. Data Architecture & Platform Design
Define end-to-end enterprise data architecture, including modern data warehouses, data lakes, and lakehouse platforms.
Design scalable, secure, and cost-effective data solutions using Snowflake and/or Databricks.
Establish data modeling standards, architecture principles, integration patterns, and technology best practices.
Design data platforms using Medallion Architecture (Bronze, Silver, Gold), dimensional modeling, and enterprise data models.
Evaluate technology choices and recommend suitable architectural solutions based on business and technical requirements.
2. Snowflake & Data Engineering
Architect data ingestion, transformation, and processing pipelines using SQL, Python, Spark, and relevant cloud-native services.
Design ELT/ETL frameworks and orchestrate data workflows across multiple enterprise systems.
Optimize query performance, compute utilization, storage, scalability, and platform costs.
Define approaches for batch and real-time/streaming data processing where required.
Establish engineering standards for reusable pipelines, testing, monitoring, CI/CD, and deployment.
3. Business Intelligence & Analytics
Design enterprise BI architecture, reporting frameworks, and self-service analytics solutions.
Strong expertise in at least one BI platform, such as Power BI, Tableau, or Qlik.
Define semantic models, dimensional models, metrics, KPIs, and business calculation standards.
Establish governed datasets, reusable business measures, and consistent reporting definitions across business functions.
Optimize BI performance, dashboard responsiveness, data refresh, and large-scale reporting workloads.
Partner with business stakeholders to translate analytical requirements into actionable insights and reporting solutions.
4. Data Governance, Quality & Security
Define data governance, data quality, metadata management, lineage, and master/reference data standards.
Implement appropriate data access controls, role-based security, masking, encryption, and compliance controls.
Establish data validation and reconciliation frameworks to ensure accuracy, consistency, and reliability.
Promote trusted, discoverable, and reusable enterprise data assets.
5. Technical Leadership & Stakeholder Management
Lead architecture discussions, technical design reviews, and solution walkthroughs.
Work closely with business leaders, product owners, data engineers, BI developers, and cloud teams.
Mentor engineering teams and establish coding, modeling, documentation, and architecture best practices.
Support presales activities, solution proposals, effort estimation, and technical presentations where required.
Evaluate emerging technologies and identify opportunities to integrate AI/GenAI into data and analytics platforms.
Required Skills & Experience
10–15+ years of experience in data engineering, data architecture, data warehousing, and analytics.
Strong hands-on architecture expertise in Snowflake
Excellent SQL skills and experience with Python, PySpark, or equivalent data processing technologies.
Strong understanding of cloud platforms such as Azure, AWS, or GCP.
Expertise in data modeling, dimensional modeling, data warehousing, lakehouse architecture, and ETL/ELT patterns.
Strong BI expertise in Power BI, Tableau, or Qlik, including semantic modeling, KPI design, and performance optimization.
Experience designing and implementing enterprise-scale data platforms and integrating data from multiple source systems.
Knowledge of data governance, security, data quality, lineage, and CI/CD practices.
Strong communication, analytical, problem-solving, and stakeholder management skills.