Company: PluginLive
About the company:
PluginLive Technology Pvt Ltd is a leading provider of innovative HR solutions. Our mission is to transform the hiring process through technology and make it easier for organizations to find, attract, and hire top talent. We are looking for a passionate and experienced Data Engineering Lead to guide the data strategy and engineering efforts for our Campus Hiring Digital Recruitment SaaS Platform.
Role Overview:
The Data Engineering Lead will be responsible for leading the data engineering team and driving the development of data infrastructure, pipelines, and analytics capabilities for our Campus Hiring Digital Recruitment SaaS Platform. This role requires a deep understanding of data engineering, big data technologies, and team leadership. The ideal candidate will have a strong technical background, excellent leadership skills, and a proven track record of building robust data systems.
Job Description
Position: Data Engineering Lead - Campus Hiring Digital Recruitment SaaS Platform
Location: Chennai
Minimum Qualification: Bachelor’s degree in computer science, Engineering, Data Science, or a related field. Master’s degree or equivalent is a plus.
Experience: 7+ years of experience in data engineering, with at least 3 years in a leadership role.
CTC: 20-30 LPA
Employment Type: Full Time
Key Responsibilities:
Data Strategy and Vision:
- Develop and communicate a clear data strategy and vision for the Campus Hiring Digital Recruitment SaaS Platform.
- Conduct market research and competitive analysis to identify trends, opportunities, and data needs.
- Define and prioritize the data roadmap, aligning it with business goals and customer requirements.
Data Infrastructure Development:
- Design, build, and maintain scalable data infrastructure and pipelines to support data collection, storage, processing, and analysis.
- Ensure the reliability, scalability, and performance of the data infrastructure.
- Implement best practices in data management, including data governance, data quality, and data security.
Data Pipeline Management:
- Oversee the development and maintenance of ETL (Extract, Transform, Load) processes.
- Ensure data is accurately and efficiently processed and available for analytics and reporting.
- Monitor and optimize data pipelines for performance and cost efficiency.
Data Analytics and Reporting:
- Collaborate with data analysts and data scientists to build and deploy advanced analytics and machine learning models.
- Develop and maintain data models, dashboards, and reports to provide insights and support decision-making.
- Ensure data is easily accessible and usable by stakeholders across the organization.
Team Leadership:
- Lead, mentor, and guide a team of data engineers, fostering a culture of collaboration, continuous improvement, and innovation.
- Conduct code reviews, provide constructive feedback, and ensure adherence to development standards.
- Collaborate with cross-functional teams including product, engineering, and marketing to ensure alignment and delivery of data goals.
Stakeholder Collaboration:
- Work closely with stakeholders to understand business requirements and translate them into technical specifications.
- Communicate effectively with non-technical stakeholders to explain data concepts and progress.
- Participate in strategic planning and decision-making processes.
Skills Required:
- Proven experience in designing and building scalable data infrastructures and pipelines.
- Strong proficiency in programming languages such as Python, R, Data visualization tools like Power BI, Tableau, Qlik, Google Analytics
- Expertise in big data technologies such as Apache Airflow, Hadoop, Spark, Kafka, and cloud data platforms like AWS, Oracle Cloud.
- Solid understanding of database technologies, both SQL and NoSQL.
- Experience with data modeling, data warehousing, and ETL processes.
- Strong analytical and problem-solving abilities.
- Excellent communication, collaboration, and leadership skills.
Preferred Qualifications:
- Experience in HR technology or recruitment platforms.
- Familiarity with machine learning and AI technologies.
- Knowledge of data governance and data security best practices.
- Contributions to open-source projects or active participation in the tech community.