Risk Analytics Revenue Assurance COE Buildout-Data and Monitoring Engineer Senior

EY- Consulting - RISK Revenue Assurance Senior-Telecom - TMT - Sector

Practice: Consulting Data Engineering & Observability (Telecom RA)

At EY youll engineer the data backbone and observability layer for a modern Revenue Assurance Solution. Your work ensures we ingest the right data at the right time with the right lineage and quality and that our monitors alerts and dashboards catch leakage quickly and reliably.

The opportunity

Youll build robust ETL/ELT pipelines data acquisition connectors and lineage tracking across BSS/OSS systems (CDRs/UDRs mediation billing CRM collections GL partner/roaming). Youll implement real-time and batch monitoring using tools like Splunk/ELK establish SLA/SLO health checks and create exception pipelines that fuel RA dashboards and workflows. Youll partner closely with the RA Risk Lead and client IT to deliver a secure scalable and observable data foundation.

Your key responsibilities

Engineering & integration

• Build and maintain ingestion and transformation pipelines (batch/streaming) from network mediation billing CRM ERP and partner systems.
• Implement data schema management survivorship rules and late arriving data handling for high-volume usage records.
• Define and maintain data lineage (e.g. Open Lineage/Atlas) and metadata for auditability and traceability.

Monitoring & observability

• Design and deploy real-time monitors (e.g. Splunk/ELK) for pipeline health data freshness volume anomalies duplication nulls and schema drifts.
• Implement SLA/SLO tracking alerting policies on-call runbooks and noise reduction strategies (alert correlation thresholds suppression windows).
• Build KRI/KPI dashboards (Power BI/Tableau/Grafana) aligned to RA risk scenarios (usage-to-cash reconciliations partner settlements discount leakage provisioning-to-billing mismatches).

Data quality & controls

• Operationalize data quality tests (e.g. completeness validity uniqueness referential integrity) and reconcile controls across systems.
• Implement exception routing (queues/webhooks) to RA workflows for triage RCA and remediation tracking.
• Ensure security privacy and compliance (access controls PII masking/tokenization data retention).

DevOps & ways of working

• Apply CI/CD for data pipelines and monitors; use Git-based workflows and environment promotion.
• Optimize performance and cost (partitioning compaction caching) and support scale testing.
• Produce high-quality documentation (data contracts runbooks deployment guides).

Skills and attributes for success

Core Skills (Must Have)

• Hands-on experience with real-time monitoring and observability tools such as Splunk and/or ELK/Elastic Stack (Beats Logstash Kibana) with the ability to configure monitors parsers and system health checks.
• Strong capability in designing automation and alerting frameworks including threshold-based rules anomaly detection SLA/SLO tracking and operational workflow triggers.
• Solid ETL/ELT knowledge applied to high volume telecom datasets (CDRs/UDRs mediation records billing extracts) with experience in data validation schema handling and ensuring pipeline reliability.
• Proficiency in SQL and Python or Scala for building monitoring scripts checks and exception-handling utilities.
• Understanding of telecom data flows across BSS/OSS and common Revenue Assurance issues such as volume irregularities mediation gaps duplication and provisioning inconsistencies.
• Ability to create clear runbooks operational documentation and collaborate effectively with RA SMEs data engineering teams and IT operations.

Preferred Skills (Good to Have)

• Exposure to stream processing and orchestration tools (Kafka Spark/Databricks Flink Airflow).
• Familiarity with data lineage/metadata platforms (Apache Atlas Open Lineage) and data quality frameworks.
• Experience with cloud platforms (Azure AWS GCP) and their data/monitoring services.
• Knowledge of IaC (Terraform) Docker/Kubernetes and secrets management.
• Understanding of anomaly detection approaches for identifying outliers or data drift.

Qualifications

• 5 years of experience in data engineering observability or monitoring roles including 3 years on telecom or adjacent high-volume data.
• Proven experience implementing production-grade monitoring and alerting across batch and real-time data environments.
• Strong command of SQL scripting (Python/Scala) and data formats such as JSON Parquet and Avro with working knowledge of Git and CI/CD.
• Demonstrated ability to produce practical operational runbooks and support stable monitoring environments.

What we look for

An engineer who blends reliability mindset with product thinking you design for scale observability and maintainability and you care about business outcomes (revenue protection) as much as pipeline performance.

What Working at EY Offers

We offer a competitive compensation package where you will be rewarded based on your performance and recognized for the value you bring to our business.

Plus we offer:

• Continuous learning: You will develop the mindset and skills to navigate whatever comes next.
• Success as defined by you: We will provide the tools and flexibility so you can make a meaningful impact your way.
• Transformative leadership: We will give you the insights coaching and confidence to be the leader the world needs.
• Diverse and inclusive culture: You will be embraced for who you are and empowered to use your voice to help others find theirs.