Data Engineering
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Key skills for this role
About the Role
Bupa is hiring a Data Engineer to design and implement robust data ingestion pipelines, enable SAS Viya Fraud, Waste, and Abuse data models, and optimize large-scale data workloads in Google BigQuery.
Key Skills for This Role
Responsibilities
- Build reusable, parameterized mappings/taskflows in Informatica IDMC
- Implement CDC, idempotent loads, schema evolution, and DQ gates
- Optimize BigQuery loads (partition/cluster, load vs. stream)
- Set up version control and CI/CD
- Profile sources; define field level mappings and rules
- Define DQ rules, exceptions, and rejects
- Parameterize taskflows; set schedules/dependencies
- Implement retries/backoff and checkpointing
- Integrate monitoring/alerts (Ops console, ChatOps)
- Define least privilege IAM and service accounts
- Apply dataset/table/row/column security & masking
- Enable audit logs and retention; classify PHI/PII
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Information Systems, or a related field
- Strong experience in ETL/ELT development using Informatica IDMC
- Proficiency in SQL and Python
- Experience with Google Cloud Platform (BigQuery, IAM)
- Experience with enterprise pipelines
- Knowledge of healthcare data (claims, providers, members)
Full Job Posting
Role Purpose
- The 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 Accountabilities Enterprise Data Ingestion and Data Engineering
- Build 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 Design
- Profile sources; define field level mappings and rules.
- Specify business logic, joins, lookups, derivations.
- Define DQ rules, exceptions, and rejects.
Orchestration, Automation & Reliability Engineering
- Parameterize taskflows; set schedules/dependencies.
- Implement retries/backoff and checkpointing.
- Integrate monitoring/alerts (Ops console, ChatOps).
Data Roles and Privacy Management
- Define 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 & Curation
- Gather 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 Optimization
- Track freshness, job health, volumes, anomalies.
- Monitor SLAs (duration, errors, cost/TB, slots).
- Tune BigQuery.
- Optimize cost (storage lifecycle, query tuning, caching).
Skills
- Data Engineering Tools: Informatica IDMC, Airflow, Apache Spark.
- Programming Languages: SQL, Python.
- Analytics Platforms: SAS Viya, SAS Enterprise Guide.
- Cloud Technologies: Google Cloud Platform (BigQuery, IAM), Azure/AWS (optional).
- Visualization Tools: Power BI, Tableau.
- Strong in BigQuery (SQL, modeling, tuning).
- Proficient with Informatica IDMC/IICS ETL/ELT.
- Experience with enterprise pipelines.
- SAS Viya (FWA) exposure is a plus.
- Knowledge of healthcare data (claims, providers, members).
- Understanding of cloud security (IAM, service accounts, private endpoints).
Education
- Bachelor’s degree in Computer Science, Information Technology, Information Systems, or a related field
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