Data Engineer

3 weeks ago

Islamabad, Islamabad, Pakistan AXIAN Group Full time

Job Title: Data Engineer (AWS + MLOps)

Department: Data & Prediction

Reports to: Head of Data & Prediction

Type: Full-time

About Axian OIF

Do you thrive in complex, dynamic environments where data-driven decisions drive significant financial and social impact? Are you passionate about mobile money's potential to revolutionize financial inclusion across Africa? If so, then this is your opportunity to lead the charge at DigiBank, a pioneering force in the African mobile money landscape.

Our mission is to empower individuals and businesses through accessible and impactful mobile financial services. We believe in the transformative power of GSM and mobile money wallets to provide a broader range of financial products and services, fostering deeper financial inclusion across Africa.

Role Overview

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 decisioning.
  • Curate a Robust Data Lakehouse
  • 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

  • Advanced degree in Information Science, Software Engineering, Data Science, Statistics, Mathematics, or a related field
  • 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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