Employment type – Full time Location – Remote Experience – 3 – 5 years Notice period – Immediate to 30 days 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. 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 environments matters as much as depth in any one stack. The role covers large datasets, cloud data platforms, and end-to-end data engineering workflows. Build and maintain scalable ETL/ELT pipelines and data models using Databricks and PySpark.

Develop data transformations and processing workflows using Python and SQL. 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.

Collaborate with analytics, BI,



and engineering teams — and directly with international clients — to deliver end-to-end data solutions. 3–5 years of experience in Data Engineering. ~ Strong hands-on experience with Databricks and Apache Spark. ~ Proficiency in PySpark, Python, and SQL. ~ Professional services client-facing experience and strong communication skills ~ Experience with lakehouses ~ Strong understanding of ETL/ELT pipelines and data modelling. ~ Working knowledge of at least one major cloud platform (AWS, Azure, or GCP) — comfort picking up a second is a plus given our multi-client environment. ~ Experience with Airflow, Databricks Workflows, or similar orchestration tools. ~ Comfortable working directly with international (primarily US) clients and adapting to a partial evening-hours overlap.

Experience with Unity Catalog or similar data governance frameworks. Familiarity with Git-based version control and CI/CD for data pipelines (e.g., Databricks Asset Bundles, Terraform). Exposure to Structured Streaming or real-time data pipelines. Databricks certification (Data Engineer Associate or Professional).

Fully

Remote work setup. Competitive compensation packages that reward high performance. Exciting growth opportunities paths and a supportive culture that facilitates continuous learning.

📌 Senior Engineer - Python & Data (India)
🏢 Fluidata Analytics
📍 India