Senior Data and Monitoring Engineer - Risk Analytics & Revenue Assurance

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

Practice : Consulting – Data Engineering & Observability (Telecom RA)

At EY, you’ll 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

You’ll build robust ETL/ELT pipelines, data acquisition connectors and lineage tracking across BSS/OSS systems (CDRs/UDRs, mediation, billing, CRM, collections, GL, partner/roaming). You’ll 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. You’ll 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.