Chief Data Architect

3 days ago

Islamabad, Islamabad, Pakistan beBeeDataEngineer Full time 3,000,000 - 3,500,000
Job Description

We are seeking a skilled professional who will oversee the development and maintenance of data infrastructure that supports our lending models and operational processes, primarily on AWS. Your role involves assisting in the machine learning lifecycle by helping data scientists deploy, monitor, and retrain models with appropriate data at optimal times.

This position offers a unique opportunity to contribute to building the financial backbone of a leading digital bank.

Key Responsibilities

  • Build & Maintain Pipelines: Develop and operate ETL/ELT pipelines using AWS Glue, Lambda, Athena, and Step Functions. Your work will support reporting and real-time decision-making.
  • Curate a Robust Data Lakehouse: Structure and maintain our data lake with proper partitioning, schema evolution, metadata tagging, and access control across multiple jurisdictions.
  • Support MLOps Lifecycle: Collaborate with data scientists to deploy models using SageMaker Pipelines, update the Feature Store, and set up triggers for model retraining.
  • Ensure Precision & Integrity: Monitor pipeline outputs and data quality dashboards to ensure all data is accurate, traceable, and reproducible.
  • Automate, Audit & Secure: Use infrastructure-as-code tools like Pulumi or Terraform to build reproducible infrastructure, implementing logging, versioning, and KMS-encrypted security practices.
  • Collaborate with Impact: Work across analytics, engineering, and credit teams to understand operational needs and develop technical pipelines and products.

Required Skills & Experience

  • A results-driven mindset with ownership and accountability
  • 4+ years in data engineering or cloud data architecture roles
  • Solid experience with AWS data stack: S3, Glue, Athena, Lambda, Step Functions
  • Proficiency in SQL, Python, and PySpark
  • Experience with data lake architecture and handling semi-structured data (Parquet, JSON)
  • Experience with MLOps, model deployment pipelines, and monitoring
  • Exposure to infrastructure-as-code (Pulumi preferred, Terraform acceptable)
  • Knowledge of secure data handling and anonymization best practices

Nice to Have

  • Experience with event-driven data flows (e.g., Kafka, EventBridge)
  • Familiarity with SageMaker Feature Store and SageMaker Pipelines
  • Background in financial services, credit scoring, or mobile money ecosystems
  • Passion for building ethical, inclusive financial systems

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