Data Engineer
1 Nos.
155731
Full Time
4.0 Year(s) To 5.0 Year(s)
8.00 LPA TO 10.00 LPA
IT Software- DBA / Datawarehousing
Steel/Metal/Iron/Non-ferrous
Job Description:
Role Overview
We are looking for an experienced Data Engineer with 4–5 years of hands-on experience in building scalable data pipelines, managing large datasets, and designing efficient data architectures.
Key Responsibilities
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Design, develop, and maintain scalable data pipelines for batch and real-time processing.
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Build and optimize ETL/ELT workflows to integrate data from multiple sources.
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Develop and optimize complex SQL queries, database schemas, and data models.
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Work with analytical databases and data warehouses to support business intelligence and reporting.
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Implement data ingestion pipelines using APIs, databases, event streams, and files.
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Ensure data quality, consistency, reliability, and governance.
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Optimize pipeline performance, query execution, storage, and infrastructure costs.
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Collaborate with backend engineers, product teams, and business stakeholders.
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Implement monitoring, logging, error handling, and automated recovery for data pipelines.
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Maintain technical documentation and follow engineering best practices.
Required Skills
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Experience: 4–5 years in data engineering or a similar role.
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Programming: Strong proficiency in Python.
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Databases: Advanced SQL and hands-on experience with MySQL or PostgreSQL.
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Data Processing: Experience building ETL/ELT pipelines and data transformation workflows.
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Analytical Databases: Hands-on experience with ClickHouse.
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Cloud: Practical experience with AWS services such as S3, Glue, Lambda, Athena, or EMR.
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Big Data: Working knowledge of Apache Spark or PySpark.
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Streaming: Understanding of Apache Kafka or other event-streaming technologies.
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Orchestration: Experience with Apache Airflow or similar workflow orchestration tools.
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DevOps: Familiarity with Docker, Git, CI/CD, and monitoring tools.
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Strong understanding of data modelling, partitioning, indexing, and query optimization.
Preferred Qualifications
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Experience handling high-volume transactional and analytical datasets.
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Experience with CDC (Change Data Capture) and incremental data loading.
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Familiarity with lakehouse architecture and data formats such as Parquet.
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Experience building near-real-time analytics and reporting platforms.
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Knowledge of data security, access control, and data governance.
What We Expect
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Strong problem-solving and analytical skills.
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Ability to independently own data pipelines from design to production.
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Focus on reliability, scalability, performance, and maintainability.
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Ability to work effectively with cross-functional engineering teams.
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A proactive approach to identifying and resolving data quality and performance issues.
Success Metrics
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Reliability and freshness of data pipelines.
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Reduction in data processing time and infrastructure costs.
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Accuracy and consistency of analytical datasets.
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Performance and scalability of data infrastructure.
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Timely delivery of business-critical data requirements.
Company Profile
We are one of the leading primary --- producers in India, --- TMT Rebar and Structural ---. Guided by a philosophy to produce safe and sustainable ---, it is a pioneer in quality --- products, operating with cutting-edge technology in order to meet the stringent requirements of its reputed customers both in India and abroad.
Operating for over six decades and now an INR 25 billion group, we have emerged as a large, growing, competitive, and multi-product --- organization by delivering quality material through innovation, excellence, and dedication.
Apply Now
- Interested candidates are requested to apply for this job.
- Recruiters will evaluate your candidature and will get in touch with you.