We are looking for a skilled Data Engineer to design, build, and optimise our modern data platform on the cloud. You'll be responsible for architecting scalable, secure, and automated data pipelines and enabling data-driven applications and AI/ML solutions across the organisation.

This is an exciting opportunity to shape the data foundation of a growing business, leveraging a modern AWS and engineering ecosystem.

Must Haves:

• 3-5 years of experience in data engineering or a similar role working with large-scale, distributed data systems.
• Strong proficiency in Python, SQL, and data modelling for analytical and transactional systems.
• Deep understanding of modern AWS data and analytics services (e.g., S3, Glue, Lambda, Redshift, or equivalents).
• Experience with Apache Spark / PySpark for batch and stream processing.
• Solid knowledge of data governance, security, and compliance frameworks.
• Familiarity with Infrastructure as Code (Terraform, CloudFormation) and CI/CD practices.
• Understanding of AI/ML data workflows, including feature engineering and data preparation for LLMs or predictive models.
• Strong problem-solving, collaboration, and communication skills.

Preferred (Nice to Have)

• Knowledge of containerization (Docker, ECS, EKS) or serverless data architectures.
• Understanding of AI/ML and NLP technologies, including integration of LLMs, automation frameworks, and RPA tools for intelligent data workflows.
• Awareness of MLOps pipelines, model monitoring, and feature store management.

Responsibilities:

• Design, build, and maintain large-scale, distributed, and event-driven data pipelines using modern AWS Data Engineering services (e.g., Glue, Lambda, Step Functions, etc.).
• Develop ETL/ELT workflows integrating structured and unstructured data into Snowflake, Redshift, and S3-based data lakes.
• Architect and optimise data ingestion, transformation, and storage layers for structured and unstructured data in a data lake or warehouse environment.
• Implement and enforce data security, governance, and access controlincluding encryption, IAM, auditing, and compliance with best practices.
• Develop and maintain metadata management, data lineage, and cataloguing frameworks to ensure traceability and consistency across datasets.
• Automate infrastructure provisioning using Infrastructure-as-Code (IaC) tools such as Terraform or AWS CloudFormation.
• Collaborate with analytics and AI/ML teams to deliver clean, high-quality, and feature-ready data for training and inference pipelines.
• Integrate observability and monitoring into data workflows to ensure reliability, performance, and cost efficiency.
• Contribute to CI/CD pipelines and Git-based version control for data workflows and infrastructure changes.
• Mentor junior engineers and champion engineering best practices for data quality, reliability, and scalability.

Other Details

• Work Days: Monday-Friday (3 pm - 12 am)
• Office location: Off to Shahrah-e-Faisal, PECHS, Karachi