LIXIL is hiring for an FRESHER entry level Data Engineer role in India

Position:

• Data Engineer

Company:

• LIXIL INDIA PVT LTD

Location:

• India

Job type:

• Full Time

Job mode:

• Remote

Job requisition id:

• 242

Years of experience:

• 0 to 3 years

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Company description

• LIXIL is an international organization working in the housing and water technology sector with the aim of improving everyday living through innovative home solutions. The company focuses on designing and delivering products that support better housing experiences and improved water technologies for people across the world. With a mission centered around enabling better homes for everyone, the organization continuously invests in research, design, engineering, and technology to create meaningful solutions that positively impact people's lives.

• The company owns and manages several globally recognized brands that have played an important role in shaping the housing and bathroom technology industry. Some of these brands include INAX, American Standard, GROHE, and TOSTEM. Through these brands, LIXIL provides products and solutions that are used in homes, buildings, and infrastructure projects across many regions.

• LIXIL products reach more than a billion individuals on a daily basis through a wide network of operations, partners, and distribution channels. The company focuses not only on product innovation but also on sustainability and responsible business practices. Environmental responsibility, resource efficiency, and long term impact are important considerations in the way the organization designs its technologies and runs its operations.

• The company also promotes a work environment where employees are encouraged to share ideas, collaborate across teams, and contribute to solving real world challenges. The culture encourages creativity, ownership, and initiative, enabling employees to participate in shaping the future of housing and water solutions.

• LIXIL believes that global progress in housing technology requires collaboration between experts from different domains such as engineering, data, design, manufacturing, and digital systems. As the world evolves with technological progress and changing consumer needs, the company continues to invest in digital transformation and modern data infrastructure to support smarter decision making and operational efficiency.

• Employees joining LIXIL become part of a global organization that values inclusivity, innovation, and responsibility. The company aims to create an environment where professionals can grow their careers while contributing to solutions that improve everyday living conditions around the world.

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Profile overview

• The Data Engineer position focuses on building and supporting modern data systems that allow organizations to manage and analyze large volumes of data effectively. This role involves working with data pipelines, storage systems, and processing frameworks to ensure that business teams have access to reliable and structured information that can support decision making and analytics.

• Professionals in this role help create systems that collect data from multiple internal and external sources, process the information, and store it in centralized platforms where analysts and business users can access it easily. These systems play an important role in supporting analytics initiatives, business intelligence dashboards, operational reporting, and advanced data science projects.

• The position requires working closely with teams responsible for analytics, reporting, and business operations. By understanding the data needs of these teams, the Data Engineer helps design systems that allow efficient access to accurate and timely information.

• Another important responsibility of the role involves maintaining data quality and ensuring that information stored within enterprise systems remains reliable and consistent. This includes implementing validation mechanisms, transformation processes, and monitoring systems that detect potential issues in data flows.

• The role also involves optimizing data infrastructure so that it can handle increasing data volumes while maintaining strong performance. As organizations adopt modern cloud platforms and distributed systems, the Data Engineer contributes to building scalable solutions that can grow with the needs of the business.

• This position supports collaboration across multiple technical and functional teams, including data analysts, software engineers, system administrators, and business stakeholders. Through these collaborations, the Data Engineer helps translate business requirements into technical data systems that enable efficient data usage across the organization.

• The role offers opportunities to work with modern cloud data technologies, real time data processing frameworks, and data integration tools that support enterprise scale data management. By contributing to these systems, the Data Engineer plays a key role in supporting data driven strategies and improving operational insights across the organization.

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Qualifications

• Strong foundation in programming languages commonly used in data engineering environments, including Python, SQL, and Java. These programming skills are used to build data transformation scripts, automate workflows, and develop scalable data processing systems.

• Understanding of modern cloud based data platforms and storage solutions that allow organizations to manage large volumes of structured and unstructured data efficiently. Examples include cloud data warehouses and large scale data processing platforms.

• Familiarity with tools used for building and managing automated data pipelines. These tools help schedule and coordinate data workflows that extract information from various sources, transform it into usable formats, and load it into centralized repositories.

• Knowledge of technologies used for data integration and data movement between systems. This includes experience with tools such as Apache Airflow, Informatica, Talend, SAP BODS, or similar pipeline orchestration platforms.

• Understanding of real time data processing frameworks that allow organizations to process and analyze streaming data as it is generated. These systems help support applications that require near real time insights.

• Familiarity with software development practices such as version control and automated deployment pipelines. Tools like Git and CI or CD systems help maintain organized code repositories and enable efficient collaboration among development teams.

• Awareness of infrastructure automation practices used to manage cloud resources through configuration scripts. Tools like Terraform allow engineers to define infrastructure configurations programmatically and maintain consistent environments.

• Knowledge of enterprise systems and business platforms such as SAP ERP. Understanding how enterprise systems generate and store data helps ensure accurate integration with analytics platforms.

• Exposure to data visualization and reporting platforms used by analysts and business teams. Examples include tools that support dashboards and visual reporting to help decision makers interpret business information.

• Ability to communicate clearly with both technical and non technical stakeholders. Since the role involves collaboration with multiple teams, clear communication helps translate business data requirements into technical solutions.

• Strong analytical thinking and problem solving abilities to identify inefficiencies in data systems and implement improvements that enhance performance and reliability.

• Interest in learning modern data technologies and continuously improving skills related to cloud computing, data engineering frameworks, and enterprise analytics platforms.

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Additional info

• The Data Engineer role involves designing and maintaining automated pipelines that move data from operational systems into centralized data platforms. These pipelines help ensure that data collected across different systems becomes accessible for reporting, analytics, and decision making activities.

• A key part of the role includes implementing processes that standardize and clean data before it enters analytics systems. By ensuring that data is structured and validated properly, the engineer helps maintain reliable datasets that analysts can trust.

• The position also requires continuous monitoring of data infrastructure to ensure that pipelines run smoothly and that data flows remain uninterrupted. This includes identifying potential performance issues, fixing errors in data transformations, and improving the efficiency of data workflows.

• Data engineers collaborate closely with analytics teams to understand what data is required for reporting or analysis. Based on these requirements, they design pipelines that deliver relevant information in structured formats that analysts can easily use.

• The role supports development of enterprise data warehouses and data lakes that store large collections of structured and semi structured data. These platforms serve as centralized systems where data from multiple business units can be integrated.

• Security and governance practices are also important aspects of the position. Data engineers help implement policies that protect sensitive information while ensuring compliance with internal guidelines and external regulatory requirements.

• The position may also involve building systems that support near real time data ingestion. Such systems allow organizations to monitor operations continuously and respond quickly to emerging trends or issues.

• Collaboration with software development teams is common in this role, particularly when integrating operational applications with data platforms. Engineers help ensure that application data is captured and transferred to analytics systems in reliable ways.

• The position provides exposure to a wide range of technologies used in modern data ecosystems. Professionals working in this role often gain experience in cloud computing platforms, pipeline orchestration tools, database systems, and data processing frameworks.

• The role also supports long term digital transformation initiatives within the organization. By building reliable data systems and scalable infrastructure, the Data Engineer helps the company make better decisions based on accurate and timely information.

Please click here to apply.