Big Data Solutions Architect

5 days ago


Lahore, Punjab, Pakistan ACE Money Transfer Full time
Role Summary:

We are seeking a highly skilled Big Data Solutions Architect to join our team at ACE Money Transfer. As a key member of our data architecture team, you will be responsible for designing and implementing scalable and high-performance data systems to support our business operations.

Key Responsibilities:
  • Big Data Solutions: Design and implement big data solutions to process large volumes of data efficiently and effectively.
  • Data Pipeline Design: Design, develop, and manage robust data pipelines and ETL processes to extract, transform, and load data from various sources into data warehouses or data lakes.
  • Real-Time Data Processing: Design and implement real-time data processing pipelines using tools such as Kafka, Spark Streaming, or Flink to handle continuous data streams effectively.


Data Modeling and Schema Design: Collaborate with stakeholders to understand data requirements and design appropriate data models and database schemas that meet business needs.

Pipeline Optimization: Optimize data pipelines and ETL processes to enhance performance and efficiency, ensuring timely and accurate data delivery to end-users.

Data Quality and Reliability: Monitor, troubleshoot, and resolve issues related to data quality, consistency, and integrity to ensure the reliability and accuracy of data systems.

End-to-End Data Solutions: Architect and implement end-to-end data solutions, including data ingestion, processing, storage, and access layers, ensuring scalability and performance.

Mentorship & Team Leadership: Mentor and guide a team of data engineers, fostering a collaborative and high-performing culture. Provide thought leadership in data engineering practices and promote knowledge-sharing initiatives.

Data Governance: Implement and maintain data governance policies, ensuring compliance with data privacy and security regulations.

Cross-Functional Collaboration: Work closely with software engineers, infrastructure teams, and other cross-functional partners to optimize data infrastructure and ensure seamless integration with other systems.

Innovation and Continuous Improvement: Stay current with industry trends and technologies in data engineering, recommending innovative solutions to improve processes and systems.

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