Manager - Data Engineering

Manager - Data Engineering

The Manager - Data Engineering role at Bupa Arabia involves designing and implementing robust data ingestion pipelines, enabling SAS Viya Fraud, Waste, and Abuse (FWA) data models, and optimizing large-scale data workloads in Google BigQuery. The ideal candidate will possess 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, and 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, and 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:

The successful candidate will demonstrate proficiency in the following areas:

• 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 expertise in BigQuery (SQL, modeling, tuning) and proficiency with Informatica IDMC/IICS ETL/ELT are essential. Experience with enterprise pipelines is required, and exposure to SAS Viya (FWA) is a significant plus. Knowledge of healthcare data (claims, providers, members) and understanding of cloud security (IAM, service accounts, private endpoints) are also critical.

Education:

Bachelor’s degree in Computer Science, Information Technology, Information Systems, or a related field is required.

Key skills/competency:

• Data Engineering
• Informatica IDMC
• Google BigQuery
• SQL
• Python
• ETL/ELT
• Cloud Data Platforms
• SAS Viya
• Healthcare Data Models
• Data Privacy