Sr data engineer

Kadel Labs

Bengaluru

Hybrid

INR 3,000,000 - 5,000,000

Full time

4 days ago

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Job summary

Kadel Labs seeks a Senior Data Engineer in Bengaluru to design, build, automate, and maintain scalable data pipelines for ML and analytics. You will work with Azure-based data platforms, ensure data quality, and collaborate with Data Scientists and ML Engineers across regional teams.

Hybrid work model (3 days from office) with day shifts, focusing on production-grade data engineering practices, dataset management, and reliable data availability for stakeholders.

Qualifications

Strong hands‑on experience in Azure Data Engineering.

Responsibilities

Design, develop, and automate scalable data pipelines.

Skills

Azure Data Engineering

Data pipelines

Azure-based data platforms

Data preparation

Data cleansing

Data quality management

Machine Learning/Analytics

Enterprise data engineering

Collaboration with Data Scientists

Model monitoring (good to have)

Job description

Job Description:

About Us:

Kadel Labs is a leading IT services company delivering top-quality technology solutions since 2017, focused on enhancing business operations and productivity through tailored, scalable, and future-ready solutions. With deep domainexpertiseand a commitment to innovation, we help businesses stay ahead of technological trends. As a CMMI Level 3 and ISO 27001:2022 certified company, we ensure best-in-class process maturity and information security, enabling organizations to achieve their digital transformation goals with confidence and efficiency.

Senior Data Engineer – Bangalore (Hybrid)

Job Description

We are looking for a Senior Data Engineer with strong expertise in Azure Data Engineering to design, build, automate, and maintain scalable data pipelines supporting Machine Learning and Analytics initiatives.

The ideal candidate will have hands‑on experience with Azure-based data platforms, data pipeline automation, dataset management, data quality, and enterprise data engineering practices. The role requires close collaboration with Data Scientists, ML Engineers, and regional teams to ensure reliable data availability, efficient data refresh cycles, and operational excellence across production data pipelines.

Role Type: Technical

Location: Bangalore

Work Mode: Hybrid – 3 days from office

Shift: Normal/Day Shift

Key Responsibilities

Data Pipeline Development & Automation

Design, develop, and automate scalable data pipelines for dynamic and frequently changing datasets.
Build robust data workflows to support Machine Learning and Analytics use cases.
Optimize data compilation and processing workflows to improve data refresh frequency and efficiency.
Ensure reliable and timely availability of data for downstream applications and stakeholders.

Model Dataset Management

Compile, prepare, and manage datasets required for ML models and analytical initiatives.
Develop processes to support timely dataset refresh requests.
Generate and maintain model datasets using the latest available data based on business and stakeholder requirements.
Ensure datasets meet required standards for accuracy, completeness, and usability.

Data Quality & Data Preparation

Perform data cleansing, validation, and quality checks across critical datasets.
Identify and resolve data inconsistencies and quality issues.
Maintain high standards of data accuracy, especially for high‑priority ML and analytics projects.

Model Monitoring & Maintenance – Good to Have

Support model monitoring activities to identify model drift and performance‑related issues.
Assist in setting up monitoring mechanisms for production models.
Track and report model performance and monitoring metrics.
Help establish processes and documentation for ongoing model monitoring.

Collaboration & Handover

Collaborate closely with Data Scientists, ML Engineers, and regional teams.
Work with regional teams to transition model monitoring and operational responsibilities.
Establish clear processes, documentation, and regular monitoring cadences to ensure smooth handovers.

Project & Operational Support

Take ownership of assigned data engineering activities and deliverables.
Ensure production data pipelines operate reliably and efficiently.
Support high‑priority projects with strong attention to detail and timely execution.
Contribute to continuous improvement of data engineering processes and operational practices.

Requirements

Required Skills & Qualifications

Strong hands‑on experience in Azure Data Engineering.
Proven experience in developing and automating data pipelines.
Experience working with Azure-based data platforms.
Strong understanding of data preparation, data cleansing, and data quality management.
Experience in managing and refreshing datasets for Machine Learning and Analytics use cases.
Ability to optimize data processing workflows for performance and efficiency.
Strong understanding of enterprise data engineering best practices.
Experience collaborating with Data Scientists, ML Engineers, and cross‑functional/regional teams.
Strong analytical, problem‑solving, and communication skills.

Good to Have

Experience with model monitoring and identifying model drift.
Knowledge of production model performance monitoring and reporting.
Experience establishing monitoring processes and operational handovers.
Exposure to Machine Learning and model lifecycle management.

What You’ll Do

As a Senior Data Engineer, you will play a key role in ensuring that high‑quality, reliable, and up‑to‑date data is continuously available for ML and Analytics initiatives. You will own critical data pipeline automation, dataset management, data quality, and operational processes while working closely with technical and regional stakeholders.

Benefits

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