Senior Software Engineer

RELX

. Monitor and support production data pipelines and analytics platforms .

Posted 10/22/2026full-timeChennai • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates strong capabilities in Python development and troubleshooting, with a focus on operational efficiency and reliability in data pipelines. Proficient in monitoring, alerting, and performance analysis across cloud and on-premises environments.

Highest-signal resume keywords

Python DevelopmentObservability ExperienceAzure DatabricksWindows Server AdministrationData Integration Concepts

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonPySparkGrafanaElasticsearchAzure Log AnalyticsAmazon CloudWatchCSVJSONXMLParquet

Soft Skills

TroubleshootingAnalytical SkillsVerbal CommunicationWritten CommunicationDetail-Oriented

Tools & Technologies

Azure Data FactoryControl-MAutoSysAirflowWindows Task Scheduler

Industry Keywords

Data PipelinesOperational MetricsKPISLASLO

Tech Stack

Tools & technologies

AirflowAzureCloudDNSElasticSearchFirewallsGrafanaPySparkPython

About the role

Key responsibilities & impact

Monitor and support production data pipelines and analytics platforms
Identify opportunities to improve reliability, performance, and operational efficiency
Troubleshoot pipeline failures, data issues, application errors, and performance problems across on-premises and cloud environments
Perform root cause analysis and implement corrective actions
Communicate incidents, remediation plans, and service impacts to stakeholders
Support Python automation processes, scheduled jobs, and file transfer workflows
Administer Windows servers, including patching, software installation, vulnerability remediation, and system maintenance
Support Azure Databricks, Data Factory, Synapse, and Data Lake Storage services
Create and maintain operational documentation, diagrams, and support procedures
Design and maintain monitoring, alerting, dashboard, centralized logging, and operational reporting solutions
Define and track operational metrics, KPIs, SLAs, and SLOs
Develop proactive monitoring and automate operational tasks to improve platform reliability and observability

Requirements

What you’ll need

Strong Python development and troubleshooting skills
PySpark experience
Observability experience, including logging, monitoring, dashboard creation from logs, alerting, debugging, and performance analysis
Experience with Grafana and Elasticsearch/Kibana
Experience with Azure Log Analytics Workspace and Amazon CloudWatch Logs
Experience with Azure or other cloud platforms
Knowledge of CSV, JSON, XML, and Parquet data formats
Experience administering Windows Server environments
Knowledge of data integration concepts, file transfers, APIs, and data validation
Understanding of DNS, proxies, firewalls, VPNs, and SSL/TLS
Strong troubleshooting, analytical, verbal, and written communication skills
Ability to manage multiple priorities in a fast-paced environment
Self-motivated, detail-oriented, and eager to learn
Experience with Control-M, AutoSys, Airflow, Windows Task Scheduler, or Job Scheduler beneficial
Databricks and Azure Data Factory experience beneficial but not mandatory

Benefits

Comp & perks

Country specific benefits
Accommodations or adjustments during the recruitment process
Equal opportunity employment