Generac Power Systems

Senior Data Engineer

Generac Power Systems pune, Maharashtra, India

Electric Power Generation · 5,001-10,000 employees

Oct 16 Closes in 1d
data-engineer Principal (10+ yrs) Full-time India
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About the role

Design, build, and maintain scalable ETL/ELT pipelines while architecting data models optimized for analytics and machine learning. Collaborate with cross-functional teams to ensure data solutions meet enterprise security and compliance standards.

What they look for

Azure Data Factory Databricks Delta Lake SQL Python Spark Data Modeling ETL/ELT CI/CD Data Engineering Cloud Architecture Distributed Data Processing Azure Synapse DevOps Data Governance Infrastructure-as-code

Requirements

Requires a bachelor's degree in a technical field and over 7 years of experience in data engineering and cloud platforms. Candidates must possess strong hands-on expertise in Azure, Databricks, SQL, Python, and Spark.

Full description

We are Generac, a leading energy technology company committed to powering a smarter world.

Over the 60 plus years of Generac’s history, we’ve been dedicated to energy innovation. From creating the home standby generator market category, to our current evolution into an energy technology solutions company, we continue to push new boundaries.

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.

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