Set up and maintain monitoring dashboards for ETL jobs using Datadog, including metrics, logs, and alerts.
Monitor daily ETL workflows and proactively detect and resolve data pipeline failures or performance issues.
Create Datadog Monitors for job status (success/failure), job duration, resource utilization, and error trends.
Work closely with Data Engineering teams to onboard new pipelines and ensure observability best practices.
Integrate Datadog with tools.
Conduct root cause analysis of ETL failures and performance bottlenecks.
Tune thresholds, baselines, and anomaly detection settings in Datadog to reduce false positives.
Document incident handling procedures and contribute to improving overall ETL monitoring maturity.
Participate in on call rotations or scheduled support windows to manage ETL health.
Required Skills & Qualifications
3+ years of experience in ETL/data pipeline monitoring, preferably in a cloud or hybrid environment.
Proficiency in using Datadog for metrics, logging, alerting, and dashboards.
Strong understanding of ETL concepts and tools (e.g., Airflow, Informatica, Talend, AWS Glue, or dbt).
Familiarity with SQL and querying large datasets.
Experience working with Python, Shell scripting, or Bash for automation and log parsing.
Understanding of cloud platforms (AWS/GCP/Azure) and services like S3, Redshift, BigQuery, etc.
Knowledge of CI/CD and DevOps principles related to data infrastructure monitoring.
Preferred Qualifications
Experience with distributed tracing and APM in Datadog.
Prior experience monitoring Spark, Kafka, or streaming pipelines.
Familiarity with ticketing tools (e.g., Jira, ServiceNow) and incident management workflows.
Key Responsibilities
Set up and maintain monitoring dashboards for ETL jobs using Datadog, including metrics, logs, and alerts.
Monitor daily ETL workflows and proactively detect and resolve data pipeline failures or performance issues.
Create Datadog Monitors for job status (success/failure), job duration, resource utilization, and error trends.
Work closely with Data Engineering teams to onboard new pipelines and ensure observability best practices.
Integrate Datadog with tools.
Conduct root cause analysis of ETL failures and performance bottlenecks.
Tune thresholds, baselines, and anomaly detection settings in Datadog to reduce false positives.
Document incident handling procedures and contribute to improving overall ETL monitoring maturity.
Participate in on call rotations or scheduled support windows to manage ETL health.
Required Skills & Qualifications
3+ years of experience in ETL/data pipeline monitoring, preferably in a cloud or hybrid environment.
Proficiency in using Datadog for metrics, logging, alerting, and dashboards.
Strong understanding of ETL concepts and tools (e.g., Airflow, Informatica, Talend, AWS Glue, or dbt).
Familiarity with SQL and querying large datasets.
Experience working with Python, Shell scripting, or Bash for automation and log parsing.
Understanding of cloud platforms (AWS/GCP/Azure) and services like S3, Redshift, BigQuery, etc.
Knowledge of CI/CD and DevOps principles related to data infrastructure monitoring.
Preferred Qualifications
Experience with distributed tracing and APM in Datadog.
Prior experience monitoring Spark, Kafka, or streaming pipelines.
Familiarity with ticketing tools (e.g., Jira, ServiceNow) and incident management workflows.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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