Manager - Data Engineering (TPA)

Bupa Arabia

Jeddah

On-site

SAR 180,000 - 300,000

Full time

7 days ago
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Job summary

Bupa Arabia is seeking a Data Engineer to design and maintain analytics-ready data pipelines and models. The role focuses on reliable ingestion, data quality, privacy, and cost-efficient processing using IDMC, Airflow, and BigQuery in a cloud environment.

Responsibilities include enabling BI/reporting, building scalable data models, and collaborating with analytics teams to deliver trusted datasets for enterprise reporting and decision making.

Qualifications

  • Bachelor’s degree in CS, IT, IS, or a related field.
  • Experience building end-to-end enterprise data pipelines.
  • Proficiency in SQL and Python for data transformation.
  • Solid knowledge of GCP (BigQuery, IAM) and Informatica IDMC.

Responsibilities

  • Ingest data and build reusable mappings in Informatica IDMC.
  • Implement CDC, schema evolution, and data-quality gates.
  • Optimize BigQuery loads with partitioning and clustering.
  • Set up CI/CD pipelines and version control for data assets.
  • Profile source systems and define field-level mappings and rules.
  • Define data-quality rules, exception handling, and rejects.

Skills

Informatica IDMC
Airflow
Apache Spark
SQL
Python
BigQuery
IAM
Tableau
Power BI
Looker
Looker Studio
IICS ETL/ELT
Medallion Architecture
Data Marts & BI
Healthcare Data
Cloud Security

Education

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

Tools

IICS ETL/ELT
Informatica IDMC
Airflow
BigQuery

Job description

Job Description

Role Purpose: To ensure the organization has reliable, well-governed, and analytics-ready data by building and maintaining robust data pipelines and models. The role exists to make trusted data available securely and cost-effectively to support enterprise reporting, BI, and data-driven decision-making.

Key Responsibilities
  1. 1- Enterprise Data Ingestion and Data Engineering;
    • Build reusable, parameterized mappings and task flows in Informatica IDMC to standardize data ingestion.
    • Implement change data capture (CDC), idempotent loads, schema evolution, and data-quality gates.
    • Optimize Big Query loads using partitioning, clustering, and the appropriate load-versus-stream approach.
    • Set up version control and CI/CD pipelines for data engineering assets.
  2. 2- Data Mapping & Transformation Design;
    • Profile source systems and define field-level mappings and transformation rules.
    • Specify business logic, including joins, lookups, and derivations.
    • Define data-quality rules, exception handling, and reject criteria.
  3. 3- Orchestration, Automation & Reliability Engineering;
    • Parameterize task flows and configure schedules and dependencies.
    • Implement retries, backoff, and checkpointing to ensure reliable processing.
    • Integrate monitoring and alerting through the Ops console and ChatOps.
  4. 4- Data Roles and Privacy management;
    • Define least-privilege IAM roles and service accounts for data access.
    • Apply dataset, table, row, and column-level security and data masking.
    • Enable audit logging and retention policies, and classify PHI/PII data.
  5. 5- Modern Data Architecture & Data Modelling;
    • Implement Medallion Architecture across the Bronze, Silver, and Gold layers.
    • Develop scalable, curated data models for analytical and reporting needs.
    • Define data quality, lineage, and governance standards for curated data.
    • Collaborate with business and analytics teams to create trusted datasets.
  6. 6- Workload Monitoring, Performance & Cost Optimisation;
    • Track data freshness, job health, volumes, and anomalies.
    • Monitor SLAs across job duration, errors, cost per TB, and slot usage.
    • Tune BigQuery performance through query optimisation and resource management.
    • Optimize cost through storage lifecycle management, query tuning, and caching.
Skills
  • Data Engineering Tools: Informatica IDMC, Airflow, Apache Spark.
  • Programming Languages: SQL, Python.
  • Cloud Technologies: Google Cloud Platform (BigQuery, IAM), Azure/AWS (optional).
  • Visualization & BI Platforms: Power BI, Looker, Looker Studio, Tableau.
  • Strong in BigQuery (SQL, modelling, tuning).
  • Proficient with Informatica IDMC/IICS ETL/ELT.
  • Experience with end-to-end enterprise data pipelines using GCP and Informatica IDMC.
  • Knowledge of Medallion Architecture.
  • Experience building reporting-ready data marts and BI datasets.
  • Experience supporting enterprise BI dashboards and self-service analytics is preferred.
  • 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

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