Data Engineer – Chennai

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1+ years of relevant experience3 days ago

Experience1+ years of relevant experience

QualificationBachelor’s degree or an equivalent combination of education and experience

Key Responsibilities

The selected candidate will develop and maintain data engineering solutions while working with stakeholders to understand business requirements. The key responsibilities include the following.
Design and develop data pipelines for efficient data collection and processing.
Build workflows that move information between relevant systems and destinations.
Maintain existing pipelines and improve their reliability.
Support the efficient processing of data required for business activities.
Investigate and address issues that affect pipeline execution or output quality.
Build and maintain scalable data storage solutions.
Organize data to support business and analytical requirements.
Help ensure that stored data remains accessible and suitable for intended uses.
Contribute to the maintenance and improvement of data architecture.
Validate incoming and processed data.
Perform or support data cleansing to correct quality issues.
Identify inconsistencies, invalid records, and unexpected data patterns.
Help maintain confidence in the accuracy of data used by downstream processes.
Investigate issues and contribute to practical corrective solutions.
Implement transformation techniques to prepare data for analysis.
Translate business data requirements into appropriate processing steps.
Support the conversion of raw data into useful, structured outputs.
Maintain transformation logic as requirements change.
Collaborate with cross-functional teams to understand data requirements.
Communicate technical considerations and possible solutions.
Work with stakeholders to ensure that data engineering solutions meet business needs.
Coordinate activities and help resolve issues affecting data delivery.
Optimize data engineering processes for performance and reliability.
Identify processing bottlenecks and opportunities for improvement.
Improve pipeline execution and data-handling efficiency.
Help maintain reliable processes that consistently deliver the expected data outputs.
The role involves developing and maintaining data pipelines, building scalable storage solutions, validating and cleansing data, implementing transformations, collaborating with stakeholders, and optimizing data engineering processes for performance and reliability.

Skills & Eligibility

The stated minimum qualification is a bachelor’s degree , or an equivalent combination of education and experience.
The supplied recruitment summary mentions B.E., B.Tech, B.Sc, and BCA. However, the detailed minimum qualification uses broader wording rather than listing every accepted degree. Applicants should confirm that their educational background qualifies for this particular position before applying.
Candidates should have at least one year of relevant experience , subject to the stated education or equivalent-experience requirement.
Relevant experience may include work involving data processing, data pipelines, data storage, data transformation, data validation, or related engineering activities. Candidates should demonstrate their actual responsibilities and technical contributions rather than relying on job titles alone.
Data pipeline development is a central responsibility of the position. Candidates should understand how to design workflows that collect data, process it, and make it available for downstream business needs.
Useful concepts include source systems, data ingestion, processing stages, transformation logic, output destinations, error handling, and monitoring. Applicants should also understand why reliability and consistency matter when pipelines run repeatedly or handle large volumes of data.
The job description requires building and maintaining scalable data storage solutions. Candidates should understand how data is organized, stored, retrieved, and prepared for different uses.
Applicants should be able to discuss the design choices they have made in relevant projects, including how data structures and processing approaches support application or reporting requirements.
Data quality is another key requirement. The role involves validation and cleansing processes to help ensure that data is accurate, consistent, and suitable for its intended purpose.
Useful areas to understand include missing values, duplicate records, invalid formats, inconsistent fields, unexpected record counts, and discrepancies between source and processed data.
The job requires implementing data transformation techniques to prepare information for analysis. Candidates should understand how raw data may need to be cleaned, standardized, combined, or converted into a format that supports downstream processing and business requirements.
The role requires working with cross-functional teams to understand data needs and develop suitable solutions. Candidates should be able to investigate data-related issues, communicate their findings, and explain how an engineering solution addresses a business requirement.
Problem-solving and practical analysis are important when diagnosing processing failures, identifying data inconsistencies, and improving pipeline performance.
The stated minimum qualification is a bachelor’s degree , or an equivalent combination of education and experience.
The supplied recruitment summary mentions B.E., B.Tech, B.Sc, and BCA. However, the detailed minimum qualification uses broader wording rather than listing every accepted degree. Applicants should confirm that their educational background qualifies for this particular position before applying.
The supplied job description emphasizes data engineering fundamentals rather than specifying a detailed technology stack. Candidates should highlight the following capabilities where they have relevant experience:
Data pipelines: Designing, developing, maintaining, and troubleshooting data-processing workflows.
Data architecture: Organizing data and supporting appropriate storage solutions.
Data storage: Maintaining scalable solutions for business data.
Data validation: Checking data accuracy, completeness, consistency, and validity.
Data cleansing: Identifying and correcting quality issues.
Data transformation: Preparing raw data for reporting or analysis.
Performance optimization: Improving pipeline efficiency and reliability.
Problem-solving: Investigating errors and identifying suitable corrective actions.
Collaboration: Gathering requirements and working with cross-functional stakeholders.
Communication: Explaining technical work and documenting relevant decisions.
The supplied description does not explicitly name required programming languages, databases, orchestration tools, or cloud platforms. Candidates should not assume that any particular tool is mandatory unless the current official application page specifies it.
The stated minimum qualification is a bachelor’s degree or an equivalent combination of education and experience. The supplied recruitment summary lists B.E., B.Tech, B.Sc, and BCA, but candidates should verify their exact qualification on the official application page.
October 20, 2026

Note: This job is posted on external sites. Joblit shares the listing for convenience and does not take responsibility for third-party content.

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