Senior Data Engineer

4 weeks ago

Islamabad, Islamabad, Pakistan DPL Full time

We're looking for a Data Engineer who understands that behind every row of data is a human decision. You'll be responsible for building and maintaining the data infrastructure that fuels our lending models and powers our operations — all on AWS.
You'll also support the machine learning lifecycle — helping our data scientists deploy, monitor, and retrain models with the right data at the right time.

This isn't just a job. It's a chance to help build the financial backbone of one of Africa's most ambitious digital banks.

Key Responsibilities

· Build & Maintain Pipelines
Develop and operate ETL/ELT pipelines using AWS Glue, Lambda, Athena, and Step Functions. Your work supports both reporting and real-time decision-making.

· Curate a Robust Data Lake house
Structure and maintain our data lake with proper partitioning, schema evolution, metadata tagging, and access control — all across multiple jurisdictions.

· Support MLOps Lifecycle
Work closely 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. Every number we serve must be accurate, traceable, and reproducible — always.

· Automate, Audit & Secure
Use infrastructure-as-code (Pulumi or Terraform) to build reproducible infrastructure. Implement logging, versioning, and KMS-encrypted security practices.

· Collaborate with Impact
Work across analytics, engineering, and credit teams to understand operational needs and translate them into technical pipelines and products.

Required Skills & Experience

· Willing to take ownership (not just pass the buck)

· Willing to learn

· 4+ years in data engineering or cloud data architecture roles

· Solid experience with AWS data stack: S3, Glue, Athena, Lambda, Step Functions

· Proficient in SQL, Python, and PySpark

· Comfort 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)

· Familiarity with 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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