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Provide L2/L3 support for data warehouse and analytics applications
Monitor data pipelines, ETL jobs, batch processes and data loads
Troubleshoot and resolve production incidents within SLA timelines
Perform root cause analysis and put preventive measures in place
Validate data integrity, quality and reconciliation processes
Provide L2/L3 support for Data Warehouse and Analytics applications.
Monitor data pipelines, ETL jobs, batch processes, and data loads.
Troubleshoot and resolve production incidents within SLA timelines.
Perform root cause analysis (RCA) and implement preventive measures.
Validate data integrity, quality, and reconciliation processes.
Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 1
Early. Similar jobs usually come down between day 6 and day 56.
From 13,630 similar postings that came down. Coming down is not always a hire.
357 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Job Summary Job Description (JD) – Application Support Engineer (Data & Analytics / Data Warehouse) Position: Application Support Engineer – Data & Analytics (Data Warehouse) Experience: 4-8 Years Location: As per business requirement Job Summary We are seeking an experienced Application Support Engineer to support and maintain enterprise Data Warehouse and Analytics platforms. The role involves monitoring, troubleshooting, resolving production incidents, ensuring data availability, and supporting ETL and reporting processes across AWS, Hadoop, Netezza, and SSIS environments. Key Responsibilities Provide L2/L3 support for Data Warehouse and Analytics applications. Monitor data pipelines, ETL jobs, batch processes, and data loads. Troubleshoot and resolve production incidents within SLA timelines. Perform root cause analysis (RCA) and implement preventive measures. Support AWS, Hadoop, Netezza, and SSIS-based data platforms. Validate data integrity, quality, and reconciliation processes. Manage job scheduling, performance tuning, and capacity monitoring. Coordinate with development, infrastructure, and business teams for issue resolution. Support release deployments, change management, and maintenance activities. Prepare operational documentation, runbooks, and incident reports. Required Skills Strong experience in Application Support and Production Support. Hands-on experience with AWS services (EC2, S3, RDS, CloudWatch). Good knowledge of Hadoop Ecosystem (HDFS, Hive, Spark). Experience with IBM Netezza Data Warehouse. Strong expertise in SSIS (SQL Server Integration Services). Knowledge of SQL, ETL processes, and Data Warehousing concepts. Experience with monitoring, incident management, and troubleshooting. Understanding of batch scheduling tools and support processes. Preferred Skills Experience with Data Analytics and Reporting platforms. Knowledge of Shell/Python scripting. Exposure to DevOps and automation tools. ITIL Incident, Problem, and Change Management knowledge. Key Responsibilities
Key Responsibilities Job Description (JD) – Application Support Engineer (Data & Analytics / Data Warehouse) Position: Application Support Engineer – Data & Analytics (Data Warehouse) Experience: 4-8 Years Location: As per business requirement Job Summary We are seeking an experienced Application Support Engineer to support and maintain enterprise Data Warehouse and Analytics platforms. The role involves monitoring, troubleshooting, resolving production incidents, ensuring data availability, and supporting ETL and reporting processes across AWS, Hadoop, Netezza, and SSIS environments. Key Responsibilities Provide L2/L3 support for Data Warehouse and Analytics applications. Monitor data pipelines, ETL jobs, batch processes, and data loads. Troubleshoot and resolve production incidents within SLA timelines. Perform root cause analysis (RCA) and implement preventive measures. Support AWS, Hadoop, Netezza, and SSIS-based data platforms. Validate data integrity, quality, and reconciliation processes. Manage job scheduling, performance tuning, and capacity monitoring. Coordinate with development, infrastructure, and business teams for issue resolution. Support release deployments, change management, and maintenance activities. Prepare operational documentation, runbooks, and incident reports. Required Skills Strong experience in Application Support and Production Support. Hands-on experience with AWS services (EC2, S3, RDS, CloudWatch). Good knowledge of Hadoop Ecosystem (HDFS, Hive, Spark). Experience with IBM Netezza Data Warehouse. Strong expertise in SSIS (SQL Server Integration Services). Knowledge of SQL, ETL processes, and Data Warehousing concepts. Experience with monitoring, incident management, and troubleshooting. Understanding of batch scheduling tools and support processes. Preferred Skills Experience with Data Analytics and Reporting platforms. Knowledge of Shell/Python scripting. Exposure to DevOps and automation tools. ITIL Incident, Problem, and Change Management knowledge. Skill Requirements
Skill Requirements Job Description (JD) – Application Support Engineer (Data & Analytics / Data Warehouse) Position: Application Support Engineer – Data & Analytics (Data Warehouse) Experience: 4-8 Years Location: As per business requirement Job Summary We are seeking an experienced Application Support Engineer to support and maintain enterprise Data Warehouse and Analytics platforms. The role involves monitoring, troubleshooting, resolving production incidents, ensuring data availability, and supporting ETL and reporting processes across AWS, Hadoop, Netezza, and SSIS environments. Key Responsibilities Provide L2/L3 support for Data Warehouse and Analytics applications. Monitor data pipelines, ETL jobs, batch processes, and data loads. Troubleshoot and resolve production incidents within SLA timelines. Perform root cause analysis (RCA) and implement preventive measures. Support AWS, Hadoop, Netezza, and SSIS-based data platforms. Validate data integrity, quality, and reconciliation processes. Manage job scheduling, performance tuning, and capacity monitoring. Coordinate with development, infrastructure, and business teams for issue resolution. Support release deployments, change management, and maintenance activities. Prepare operational documentation, runbooks, and incident reports. Required Skills Strong experience in Application Support and Production Support. Hands-on experience with AWS services (EC2, S3, RDS, CloudWatch). Good knowledge of Hadoop Ecosystem (HDFS, Hive, Spark). Experience with IBM Netezza Data Warehouse. Strong expertise in SSIS (SQL Server Integration Services). Knowledge of SQL, ETL processes, and Data Warehousing concepts. Experience with monitoring, incident management, and troubleshooting. Understanding of batch scheduling tools and support processes. Preferred Skills Experience with Data Analytics and Reporting platforms. Knowledge of Shell/Python scripting. Exposure to DevOps and automation tools. ITIL Incident, Problem, and Change Management knowledge. Other Requirements
Other Requirements Job Description (JD) – Application Support Engineer (Data & Analytics / Data Warehouse) Position: Application Support Engineer – Data & Analytics (Data Warehouse) Experience: 4-8 Years Location: As per business requirement Job Summary We are seeking an experienced Application Support Engineer to support and maintain enterprise Data Warehouse and Analytics platforms. The role involves monitoring, troubleshooting, resolving production incidents, ensuring data availability, and supporting ETL and reporting processes across AWS, Hadoop, Netezza, and SSIS environments. Key Responsibilities Provide L2/L3 support for Data Warehouse and Analytics applications. Monitor data pipelines, ETL jobs, batch processes, and data loads. Troubleshoot and resolve production incidents within SLA timelines. Perform root cause analysis (RCA) and implement preventive measures. Support AWS, Hadoop, Netezza, and SSIS-based data platforms. Validate data integrity, quality, and reconciliation processes. Manage job scheduling, performance tuning, and capacity monitoring. Coordinate with development, infrastructure, and business teams for issue resolution. Support release deployments, change management, and maintenance activities. Prepare operational documentation, runbooks, and incident reports. Required Skills Strong experience in Application Support and Production Support. Hands-on experience with AWS services (EC2, S3, RDS, CloudWatch). Good knowledge of Hadoop Ecosystem (HDFS, Hive, Spark). Experience with IBM Netezza Data Warehouse. Strong expertise in SSIS (SQL Server Integration Services). Knowledge of SQL, ETL processes, and Data Warehousing concepts. Experience with monitoring, incident management, and troubleshooting. Understanding of batch scheduling tools and support processes. Preferred Skills Experience with Data Analytics and Reporting platforms. Knowledge of Shell/Python scripting. Exposure to DevOps and automation tools. ITIL Incident, Problem, and Change Management knowledge.
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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.
Job Description (JD) – Application Support Engineer (Data & Analytics / Data Warehouse) Position: Application Support Engineer – Data & Analytics (Data Warehouse) Experience: 4-8 Years Location: As per business requirement Job Summary We are seeking an experienced Application Support Engineer to support and maintain enterprise Data Warehouse and Analytics platforms. The role involves monitoring, troubleshooting, resolving production incidents, ensuring data availability, and supporting ETL and reporting processes across AWS, Hadoop, Netezza, and SSIS environments. Key Responsibilities Provide L2/L3 support for Data Warehouse and Analytics applications. Monitor data pipelines, ETL jobs, batch processes, and data loads. Troubleshoot and resolve production incidents within SLA timelines. Perform root cause analysis (RCA) and implement preventive measures. Support AWS, Hadoop, Netezza, and SSIS-based data platforms. Validate data integrity, quality, and reconciliation processes. Manage job scheduling, performance tuning, and capacity monitoring. Coordinate with development, infrastructure, and business teams for issue resolution. Support release deployments, change management, and maintenance activities. Prepare operational documentation, runbooks, and incident reports. Required Skills Strong experience in Application Support and Production Support. Hands-on experience with AWS services (EC2, S3, RDS, CloudWatch). Good knowledge of Hadoop Ecosystem (HDFS, Hive, Spark). Experience with IBM Netezza Data Warehouse. Strong expertise in SSIS (SQL Server Integration Services). Knowledge of SQL, ETL processes, and Data Warehousing concepts. Experience with monitoring, incident management, and troubleshooting. Understanding of batch scheduling tools and support processes. Preferred Skills Experience with Data Analytics and Reporting platforms. Knowledge of Shell/Python scripting. Exposure to DevOps and automation tools. ITIL Incident, Problem, and Change Management knowledge.
Job Description (JD) – Application Support Engineer (Data & Analytics / Data Warehouse) Position: Application Support Engineer – Data & Analytics (Data Warehouse) Experience: 4-8 Years Location: As per business requirement Job Summary We are seeking an experienced Application Support Engineer to support and maintain enterprise Data Warehouse and Analytics platforms. The role involves monitoring, troubleshooting, resolving production incidents, ensuring data availability, and supporting ETL and reporting processes across AWS, Hadoop, Netezza, and SSIS environments. Key Responsibilities Provide L2/L3 support for Data Warehouse and Analytics applications. Monitor data pipelines, ETL jobs, batch processes, and data loads. Troubleshoot and resolve production incidents within SLA timelines. Perform root cause analysis (RCA) and implement preventive measures. Support AWS, Hadoop, Netezza, and SSIS-based data platforms. Validate data integrity, quality, and reconciliation processes. Manage job scheduling, performance tuning, and capacity monitoring. Coordinate with development, infrastructure, and business teams for issue resolution. Support release deployments, change management, and maintenance activities. Prepare operational documentation, runbooks, and incident reports. Required Skills Strong experience in Application Support and Production Support. Hands-on experience with AWS services (EC2, S3, RDS, CloudWatch). Good knowledge of Hadoop Ecosystem (HDFS, Hive, Spark). Experience with IBM Netezza Data Warehouse. Strong expertise in SSIS (SQL Server Integration Services). Knowledge of SQL, ETL processes, and Data Warehousing concepts. Experience with monitoring, incident management, and troubleshooting. Understanding of batch scheduling tools and support processes. Preferred Skills Experience with Data Analytics and Reporting platforms. Knowledge of Shell/Python scripting. Exposure to DevOps and automation tools. ITIL Incident, Problem, and Change Management knowledge.
Job Description (JD) – Application Support Engineer (Data & Analytics / Data Warehouse) Position: Application Support Engineer – Data & Analytics (Data Warehouse) Experience: 4-8 Years Location: As per business requirement Job Summary We are seeking an experienced Application Support Engineer to support and maintain enterprise Data Warehouse and Analytics platforms. The role involves monitoring, troubleshooting, resolving production incidents, ensuring data availability, and supporting ETL and reporting processes across AWS, Hadoop, Netezza, and SSIS environments. Key Responsibilities Provide L2/L3 support for Data Warehouse and Analytics applications. Monitor data pipelines, ETL jobs, batch processes, and data loads. Troubleshoot and resolve production incidents within SLA timelines. Perform root cause analysis (RCA) and implement preventive measures. Support AWS, Hadoop, Netezza, and SSIS-based data platforms. Validate data integrity, quality, and reconciliation processes. Manage job scheduling, performance tuning, and capacity monitoring. Coordinate with development, infrastructure, and business teams for issue resolution. Support release deployments, change management, and maintenance activities. Prepare operational documentation, runbooks, and incident reports. Required Skills Strong experience in Application Support and Production Support. Hands-on experience with AWS services (EC2, S3, RDS, CloudWatch). Good knowledge of Hadoop Ecosystem (HDFS, Hive, Spark). Experience with IBM Netezza Data Warehouse. Strong expertise in SSIS (SQL Server Integration Services). Knowledge of SQL, ETL processes, and Data Warehousing concepts. Experience with monitoring, incident management, and troubleshooting. Understanding of batch scheduling tools and support processes. Preferred Skills Experience with Data Analytics and Reporting platforms. Knowledge of Shell/Python scripting. Exposure to DevOps and automation tools. ITIL Incident, Problem, and Change Management knowledge.
Job Description (JD) – Application Support Engineer (Data & Analytics / Data Warehouse) Position: Application Support Engineer – Data & Analytics (Data Warehouse) Experience: 4-8 Years Location: As per business requirement Job Summary We are seeking an experienced Application Support Engineer to support and maintain enterprise Data Warehouse and Analytics platforms. The role involves monitoring, troubleshooting, resolving production incidents, ensuring data availability, and supporting ETL and reporting processes across AWS, Hadoop, Netezza, and SSIS environments. Key Responsibilities Provide L2/L3 support for Data Warehouse and Analytics applications. Monitor data pipelines, ETL jobs, batch processes, and data loads. Troubleshoot and resolve production incidents within SLA timelines. Perform root cause analysis (RCA) and implement preventive measures. Support AWS, Hadoop, Netezza, and SSIS-based data platforms. Validate data integrity, quality, and reconciliation processes. Manage job scheduling, performance tuning, and capacity monitoring. Coordinate with development, infrastructure, and business teams for issue resolution. Support release deployments, change management, and maintenance activities. Prepare operational documentation, runbooks, and incident reports. Required Skills Strong experience in Application Support and Production Support. Hands-on experience with AWS services (EC2, S3, RDS, CloudWatch). Good knowledge of Hadoop Ecosystem (HDFS, Hive, Spark). Experience with IBM Netezza Data Warehouse. Strong expertise in SSIS (SQL Server Integration Services). Knowledge of SQL, ETL processes, and Data Warehousing concepts. Experience with monitoring, incident management, and troubleshooting. Understanding of batch scheduling tools and support processes. Preferred Skills Experience with Data Analytics and Reporting platforms. Knowledge of Shell/Python scripting. Exposure to DevOps and automation tools. ITIL Incident, Problem, and Change Management knowledge.
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