Cloud Raptor
Website:
cloud-raptor.com
Job details:
Job Description: Principal / Lead Data Architect (AWS Focus)
Location: Bengaluru Experience: 10+ Years Employment Type: Full-time
🎯 Mandatory Skills
- Databricks (Delta Lake, Unity Catalog, Spark optimization)
- Python, Scala, SQL
- Snowflake (architecture, performance tuning, cost optimization)
- Structured Streaming
- Apache Kafka, Flink, AWS Kinesis
- Cloud-native architecture (AWS ecosystem)
🏗️ Position Summary
We are seeking a highly seasoned Lead/Principal Data Architect with over a decade of experience to design, build, and scale our next-generation data platform. This role requires a rare blend of deep respect for traditional data warehousing and mastery of modern Lakehouse architectures, real-time streaming, and AI-driven data solutions.
You will act as the mastermind behind our data strategy, bridging complex business requirements with robust technical execution, while mentoring engineering teams and driving architectural excellence.
🔑 Roles & Responsibilities
- Architecture & Strategy: End-to-end design of scalable, secure, and highly available data architectures leveraging Databricks and Snowflake.
- Pipeline Engineering: Architect, optimize, and oversee deployment of reliable streaming and batch pipelines (ETL/ELT) for large-scale datasets.
- Cloud Architecture: Deploy enterprise data platform components natively within AWS, ensuring integration with IAM, networking, and security protocols.
- API Ingestion & Orchestration: Build robust ingestion frameworks using Databricks APIs and external REST/GraphQL APIs for automated workflows.
- Real-time Processing: Design frameworks for low-latency, business-critical data ingestion and processing.
- Hybrid Data Modelling: Harmonize relational warehousing (Kimball/Inmon, Star/Snowflake schemas) with modern semi/unstructured paradigms.
- Technical Leadership: Provide governance, solve complex bottlenecks, and mentor teams on best practices.
- AI Integration: Collaborate with AI/ML teams to architect data layers supporting LLMs, feature stores, and advanced analytics.
📚 Required Qualifications
- Education: B.Tech/M.Tech in Computer Science, Engineering, or related field.
- Experience: 10+ years in Data Engineering, Warehousing, and Architecture with proven leadership in enterprise-scale platforms.
- Technical Expertise:
- Databricks Lakehouse, Delta Lake, Unity Catalog
- Python, Scala, SQL for distributed pipelines
- Snowflake architecture & optimization
- Real-time systems (Kafka, Flink, AWS Kinesis)
- RDBMS + NoSQL ecosystems
🌟 Preferred Qualifications
- Exposure to AI/ML data readiness (vector databases, feature stores, LLM pipelines).
- Certifications: Databricks Certified Data Architect, Snowflake Certified Advanced Architect.
- Strong communication skills to articulate complex architectures to both technical and non-technical stakeholders.
Click on Apply to know more.