Manager - Data Engineering
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Key skills for this role
About the Role
Bupa Arabia seeks a Manager - Data Engineering to design and implement robust data ingestion pipelines, enable SAS Viya Fraud, Waste, and Abuse (FWA) data models, and optimize large-scale data workloads in Google BigQuery.
Key Skills for This Role
Responsibilities
- Build reusable, parameterized mappings/taskflows for enterprise data ingestion
- Implement CDC, idempotent loads, schema evolution, 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
- Specify business logic, joins, lookups, derivations
- 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
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 data pipelines
- Knowledge of healthcare data (claims, providers, members)
- Understanding of cloud security (IAM, service accounts, private endpoints)
- Experience with SAS Viya (FWA) is a plus
- Experience with Azure/AWS is optional
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
- 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.
- Profile sources; define field level mappings and rules.
- Specify business logic, joins, lookups, derivations.
- 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.
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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