Full-Stack Data Engineer – Data & ML Automation (Databricks) (Pune)

Codvo Private Limited; Pune District; On-site; INR 800,000 - 1,200,000; Full time

Job summary

A leading data engineering firm in Pune is seeking a Fullstack Data Engineer to develop automation tools and testing frameworks for data workflows. The ideal candidate will build internal applications using React and Databricks for better data interaction. This role emphasizes engineering best practices and a passion for solving complex data challenges in a collaborative environment. Join a dynamic team focused on innovation and growth.

Qualifications

• Experience in developing CLI tools and utilities.
• Proficient in data pipeline automation and testing.
• Familiarity with data visualization tools.

Responsibilities

• Develop CLI tools for automating workflows across data platforms.
• Design integration tests and validation frameworks for ETL/ELT pipelines.
• Build internal applications to visualize data flows and monitor performance.

Skills

Automation scripting

Data pipeline management

CLI tools development

React

Databricks

ML workflows

Tools

Power BI

Tableau

Looker

Job description

About Us

At Codvo, we are committed to building scalable, future‑ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting‑edge technology.

Overview

We are seeking a Fullstack Data Engineer who can operate at the intersection of data engineering, fullstack development, and testing/automation. This role will focus on building internal automation tooling, validating data and ML workflows, and developing lightweight web interfaces or dashboards that help teams interact with data and model outputs more effectively.

Key Responsibilities

• Automation & Tooling: develop CLI tools, scripts, and utilities to automate repetitive workflows across the data platform, such as pipeline execution, governance and metadata synchronization, environment setup, test harness creation, Databricks workflow automation, job deployment, environment provisioning, and MLOps operations.
• Data & ML Workflow Testing: design and implement integration tests, end‑to‑end pipeline tests, and validation frameworks for Databricks ETL/ELT pipelines and ML inference workflows to improve reliability, observability, and engineering productivity.
• Internal Tools & Dashboards: build quick internal applications using React, Streamlit or similar frameworks to visualize data flows, provide model inference demos, enable operational or configuration controls, and develop productivity and monitoring dashboards.
• Engineering Practices: apply best practices around spec‑driven development, coding automation patterns, and CI/CD workflows for data/ML systems.

Nice‑to‑Have Skills

Experience creating dashboards and visualizations using Databricks AI/BI or any modern BI tool (Power BI, Tableau, Looker, etc.).