Job Description

Mandatory Skills:
Spark,Databricks Engineer,Kafka,Stream Processing,SQL Development,Python,Snowflake

Skill to Evaluate:
Spark,Databricks Engineer,Snowflake SQL,Kafka,Stream Processing,SQL Development,Python,Snowflake

Architecture & Strategy: End-to-end design of scalable, secure, and highly available data architectures leveraging up-to-date cloud data ecosystems (Databricks and Snowflake).
Pipeline Engineering: Architect, optimize, and oversee the deployment of reliable streaming and batch data pipelines (ETL/ELT) to process complex, large-scale datasets.
Cloud Architecture: Architect and deploy scalable enterprise data platform components natively within the AWS ecosystem, ensuring tight integration with core security, IAM, and networking protocols.
API Ingestion & Orchestration:



Design and implement robust data ingestion frameworks leveraging Databricks APIs and external REST/GraphQL APIs for automated workflows, platform orchestration, and data delivery.
Real-time Processing: Design and implement robust frameworks for real-time data ingestion and processing to solve business-critical, low-latency use cases.
Hybrid Data Modelling: Harmonize "old school" relational data warehousing patterns (Kimball/Inmon, Star/Snowflake schemas) with unstructured/semi-structured contemporary paradigms.
Technical Leadership: Act as a core problem-solver for complex data bottlenecks, provide technical governance, and mentor engineering teams on data best practices.
AI Integration: Collaborate with Data Science and AI teams to architect data layers that seamlessly support LLMs, Machine Learning pipelines, and advanced analytics solutions.

📌 Senior Data Engineer Databricks Bengaluru
🏢 TRIGENT SOFTWARE PRIVATE
📍 Bengaluru