Reads like a Data Engineer role: pipelines and data infrastructure.
Noida, Uttar Pradesh, India
Live, first seen by us 45 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Develop, maintain and optimise ETL pipelines for extraction, transformation and loading
Write and optimise complex SQL queries, stored procedures and analytical queries
Perform data cleansing, validation and quality checks
Monitor data pipelines and troubleshoot data quality and processing issues
Analyse large datasets to find trends, patterns and discrepancies
Develop, maintain, and optimise ETL pipelines for data extraction, transformation, and loading.
Write and optimise complex SQL queries, joins, subqueries, CTEs, stored procedures, and analytical queries.
Perform data transformation, cleansing, validation, and quality checks.
Monitor data pipelines and troubleshoot data quality and processing issues.
Analyse large datasets to identify trends, patterns, and discrepancies.
Strong hands-on SQL skills – Mandatory.
2+ years of relevant experience in Data Analytics, ETL Development, Data Engineering, or similar data-focused roles.
Good understanding of ETL concepts and pipeline development.
Experience with data validation, quality checks, and troubleshooting.
Strong understanding of relational databases and data structures.
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Day 45
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Position- Data Analyst Exp- 1-6 yrs Location- Noida (Sec- 62) Notice Period- Immediate joiner- 15 days Skills- Data Analyst, ETL Developer, SQL skills (mandatory), ETL concepts, data validation, quality checks, and troubleshooting, data extraction, transformation, loading, and monitoring About the Role We are looking for a Data Analyst with strong hands-on experience in SQL and ETL pipelines. The ideal candidate should be proficient in data extraction, transformation, loading, validation, monitoring, and troubleshooting, with the ability to work with large datasets and optimise query performance. Key Responsibilities Develop, maintain, and optimise ETL pipelines for data extraction, transformation, and loading. Write and optimise complex SQL queries, joins, subqueries, CTEs, stored procedures, and analytical queries. Perform data transformation, cleansing, validation, and quality checks. Monitor data pipelines and troubleshoot data quality and processing issues. Analyse large datasets to identify trends, patterns, and discrepancies. Ensure data accuracy, consistency, and integrity across multiple data sources. Optimise SQL queries and database performance. Collaborate with technical and business teams to understand data requirements. Troubleshoot ETL and data pipeline failures and ensure timely resolution. Maintain technical documentation for data processes and pipelines. Required Skills 2+ years of relevant experience in Data Analytics, ETL Development, Data Engineering, or similar data-focused roles. Strong hands-on SQL skills – Mandatory. Good understanding of ETL concepts and pipeline development. Experience in data extraction, transformation, loading, and pipeline monitoring. Strong understanding of relational databases and data structures. Experience with data validation, quality checks, and troubleshooting. Strong analytical and problem-solving skills. Good verbal communication skills. Ability to work independently as well as collaboratively.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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Noida, Uttar Pradesh, India
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