Overview

Employment type – Full time Location – Remote Working Hours - 4:00 PM – 12:00 AM IST Experience – 3 – 5 years Notice period – Immediate to 30 days

Responsibilities

• Build and maintain scalable ETL/ELT pipelines and data models using Databricks and PySpark.
• Develop data transformations and processing workflows using Python and SQL.
• Work with Delta Lake and lakehouse architecture.
• Design and maintain data models and data marts for analytics.
• Optimize Spark jobs and SQL queries for performance and scalability.
• Implement data quality, validation, monitoring, and error handling.
• Work across cloud platforms (AWS, Azure, or GCP) depending on the client engagement.
• Manage pipeline code through Git-based version control and CI/CD workflows.
• Collaborate with analytics, BI, and engineering teams — and directly with international clients — to deliver end-to-end data solutions.

Qualifications

• Notice period – Immediate to 30 days
• About Fluidata
• Fluidata Analytics is an AI-native data and analytics firm. We design and run data systems for clients across 8 industries and 5 continents, turning messy operational data into insights leaders can act on — spanning data engineering, analytics, automation, and AI.
• Our team is made up of people who learn quick, build with intention, and work directly on challenges that shape how organizations operate and make decisions.
• About the Role
• We're looking for a Databricks Engineer to build and maintain scalable data pipelines using Databricks, PySpark, Python, and SQL. Because we work across multiple clients, you'll work with different cloud platforms (AWS, Azure, or GCP depending on the engagement) and different orchestration tools — so adaptability across settings matters as much as depth in any one stack. The role covers large datasets, cloud data platforms, and end-to-end data engineering workflows.
• Must-have 3–5 years of
• experience in Data Engineeri