Data Architect

Blumetra Solutions LLC; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Blumetra Solutions LLC is seeking an experienced Data Architect with deep expertise in Snowflake and Databricks to own end-to-end data platforms. You will design scalable data engineering and BI solutions, translate business requirements into reliable data models, and lead semantic modeling across analytics teams.

The role combines hands-on architecture with leadership, stakeholder management, and strategic guidance on cloud data platforms, governance, and AI-enabled analytics.

Qualifications

• 10+ to 15+ years in data engineering, architecture, warehousing, and analytics.
• Hands-on Snowflake and/or Databricks architecture experience.
• Strong SQL and Python skills; cloud platforms (Azure/AWS/GCP) expertise.

Responsibilities

• Define end-to-end enterprise data architecture including data warehouses, data lakes, and lakehouse platforms.
• Design scalable, secure, and cost-efficient data solutions on Snowflake/Databricks.
• Establish data modeling standards, integration patterns, and best practices.
• Lead BI architecture and semantic modelling for Power BI/Tableau/Qlik.
• Mentor teams, align with stakeholders, and drive CI/CD for data pipelines.

Skills

Snowflake

Databricks

SQL

Python

Cloud platforms

BI tools

Data modeling

ETL/ELT

CI/CD

Stakeholder management

Tools

dbt

Databricks Unity Catalog

Snowflake governance features

Kafka

Airflow

Job description

Blumetra Solutions is an AI-native data and analytics company helping enterprises modernize their data platforms, build scalable data engineering solutions, and unlock business value through advanced analytics, AI, and cloud technologies.

Role Overview

We are looking for an experienced Data Architect with strong expertise in Snowflake and/or Databricks, 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

• 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 / Databricks & 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

• 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 and/or Databricks.
• 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.

Preferred Qualifications

• Experience with dbt, Databricks Unity Catalog, Snowflake governance features, or comparable data management capabilities.
• Knowledge of Microsoft Fabric, Azure Data Factory, AWS Glue, or similar data integration services.
• Exposure to streaming technologies such as Kafka or cloud‑native streaming services.
• Experience with AI/ML platforms, GenAI-enabled analytics, or natural‑language interfaces for BI.
• Relevant Snowflake, Databricks, cloud, or BI certifications.

Ideal Candidate Profile

• The ideal candidate is a hands‑on architect who can bridge data engineering, cloud data platforms, and BI. They should be capable of defining enterprise architecture, guiding engineering implementation, and ensuring that curated data translates into trusted business insights.