Manager - Data Engineering

Role PurposeThe role involves designing and implementing robust data ingestion pipelines, enable SAS Viya Fraud, Waste, and Abuse (FWA) data models, and optimize large-scale data workloads in Google BigQuery. The ideal candidates will have strong experience in ETL/ELT development using Informatica IDMC, cloud data platforms, and healthcare data models.Key AccountabilitiesEnterprise Data Ingestion and Data EngineeringBuild reusable, parameterized mappings/taskflows.Implement CDC, idempotent loads, schema evolution, DQ gates.Optimize BigQuery loads (partition/cluster, load vs. stream).Set up version control and CI/CD.Data Mapping & Transformation DesignProfile sources; define field-level mappings and rules.Specify business logic, joins, lookups, derivations.Define DQ rules, exceptions, and rejects.Orchestration, Automation & Reliability EngineeringParameterize taskflows; set schedules/dependencies.Implement retries/backoff and checkpointing.Integrate monitoring/alerts (Ops console, ChatOps).Data Roles and Privacy managementDefine least‑privilege IAM and service accounts.Apply dataset/table/row/column security & masking.Enable audit logs and retention; classify PHI/PII.SAS Viya FWA Domain Modeling & CurationGather model inputs, features, windows, granularity.Align scoring logic and feature engineering steps.Design curated FWA datasets (claims, eligibility, providers, members, preauths).Workload Monitoring, Performance & Cost OptimizationTrack freshness, job health, volumes, anomalies.Monitor SLAs (duration, errors, cost/TB, slots).Tune BigQuery.Optimize cost (storage lifecycle, query tuning, caching).#J-18808-Ljbffr