Senior Data Engineer

Generac; Ramban district; On-site; INR 850,000 - 1,400,000; Full time

Job summary

Generac is seeking a senior Data Engineer to design, build, and maintain scalable data pipelines on Azure Databricks, enabling analytics, reporting, and ML workloads.

You will architect data models, enforce standards across CI/CD and DevOps, and collaborate with security and infrastructure teams to ensure reliability and cost efficiency in cloud environments.

Qualifications

• 7+ years of data engineering experience with cloud data platforms.
• Hands-on with Azure and Databricks pipelines.
• Strong SQL, Python, Spark, and Delta Lake skills.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines on Azure Databricks.
• Architect analytics- and ML-ready data models and storage patterns.
• Establish coding standards, CI/CD, testing, and documentation.
• Mentor data engineers and contractors; perform code reviews.

Skills

SQL

Python

Spark

ETL/ELT design

Data modeling

Cloud data platforms

Communication

Mentorship

Education

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or related field

Master’s degree in Data Engineering, Computer Science, Analytics, or related field

Tools

Azure Data Factory

Databricks

Delta Lake

Azure Synapse

DevOps

Job description

Major Responsibilities

Delivery Management & Prioritization

• Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Databricks, Delta Lake, and related Azure services.
• Architect data models and storage patterns optimized for analytics, reporting, and machine learning workloads.
• Establish and enforce engineering standards for code quality, version control, CI/CD, testing, and documentation.
• Optimize data pipelines for performance, reliability, and cost efficiency across cloud environments.

Platform Partnership & Operational Excellence

• Collaborate with cloud platform, security, and infrastructure teams to ensure data solutions meet enterprise standards for security, compliance, and reliability.
• Implement monitoring, alerting, and automated recovery processes for critical data pipelines and datasets
• Partner with analytics and business teams to understand requirements and translate them into scalable technical solutions.
• Provide technical leadership, code reviews, and mentorship to data engineers and contractors.

Minimum Job Requirements

Education

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or related field (or equivalent practical experience).

Certification / License

• Azure Data Engineer or equivalent cloud certification preferred.

Work Experience

• 7+ years of experience in data engineering, cloud data platforms, or large‑scale data architecture.
• Hands‑on experience designing and delivering data pipelines using Azure and Databricks.
• Strong experience with SQL, Python, Spark, Delta Lake, and distributed data processing.
• Experience supporting production data systems, including monitoring, troubleshooting, and performance tuning.

Knowledge / Skills / Abilities

• Deep understanding of data modeling, ETL/ELT patterns, orchestration, and data quality frameworks.
• Strong knowledge of Azure services (ADF, ADLS, Databricks, Azure SQL, Synapse, Key Vault, DevOps).
• Ability to translate business requirements into scalable technical designs
• Excellent written and verbal communication skills, including the ability to communicate complex topics to non-technical audiences.

Preferred Job Requirements

Education

• Master’s degree in Data Engineering, Computer Science, Analytics, or a related field.

Certification / License

• Preferred certifications: Microsoft Certified Azure Data Engineer, Databricks Data Engineer Professional, Agile project management.

Work Experience

• Experience leading technical design for large‑scale data engineering initiatives.
• Experience implementing Lakehouse architectures and supporting advanced analytics or ML workloads.
• Experience with CI/CD pipelines, infrastructure‑as‑code, and DevOps practices.
• Vendor and contractor oversight experience.

Knowledge / Skills / Abilities

• Strong understanding of data governance, metadata management, and enterprise data cataloging.
• Ability to drive adoption of engineering best practices and standardized ways of working across teams.