Mayuri Mane

Application Support Engineer | Data Support Engineer

Talent

PuneMember since August 20, 2026

SQLData validationFilteringJoinsAggregationsTroubleshooting queriesProduction data checksSnowflakeAzure DatabricksApache SparkApache AirflowDAG monitoringAWS S3AzureServiceNowIncident ManagementService RequestsSLA ManagementLinuxMicrosoft Office 365CI/CD monitoringPythonpower BI

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SQLData validationFilteringJoinsAggregations

About

Data / Application Support Engineer with 3+ years of experience in L1/L2 production support for enterprise data pipelines. Skilled in SQL-based data validation and troubleshooting, Apache Airflow DAG monitoring, and cloud data platforms including Azure Databricks, Snowflake, and AWS S3. Proven track record investigating job failures, resolving production incidents within SLA, and partnering with cross-functional engineering teams to maintain reliable, high-availability data operations.

Experience

Senior System Engineer - Cognizant

(2022-07 - 2026-06)

Project: Nike — End-to-End Data Pipeline. Supported enterprise data pipelines in an L1/L2 production support environment, ensuring reliable and timely execution of scheduled workloads.

Monitored and managed end-to-end data pipelines using Apache Airflow DAGs, investigating job failures, performing recovery actions, and validating successful workflow completion.
Performed SQL-based data validation and troubleshooting to identify missing, duplicate, inconsistent, or unexpected data and drive issue resolution.
Used SQL to filter, compare, and validate data across processing stages, supporting root-cause investigation of data mismatches and production issues.
Worked with Snowflake and Azure Databricks to perform data checks, monitor processing activity, and investigate pipeline-related issues.
Managed data files and storage operations in AWS S3, including file availability checks and coordination with downstream teams on file-related issues.
Handled production incidents and service requests using ServiceNow, ensuring timely resolution while maintaining defined SLA timelines.
Collaborated with development and support teams to troubleshoot recurring production and data-related issues, improving overall operational reliability.
Performed post-recovery and downstream validation to confirm data-processing workflows completed successfully end-to-end.
Authored and maintained operational reports, troubleshooting documentation, and production-support procedures to support consistent, repeatable operations.