Data Warehouse Architect and Engineer

5 days ago


Lahore, Punjab, Pakistan ACE Money Transfer Full time

About Working at ACE Money Transfer

We are a rapidly growing company committed to providing exceptional international money transfer services.

Job Role:

This role is responsible for designing and implementing data warehouse solutions that drive business decisions. As a Senior Data Engineer, you will lead the implementation of data pipelines, ETL processes, and data lake management. Your expertise will enable us to deliver high-quality data insights that drive business success.

Key Responsibilities:

  1. Data Warehouse Solutions: Design and implement scalable data warehouse solutions that handle structured and unstructured data efficiently.
  2. Data Pipeline Design: Develop robust data pipelines capable of handling both structured and unstructured data effectively.
  3. ETL Process Development: Create efficient ETL processes, including low-latency data acquisition and stream processing using tools like Glue or Spark.
  4. Data Lake Management: Manage and optimize the data lake on AWS, ensuring efficient data storage, retrieval, and transformation.
  5. Data Governance and Quality: Establish data quality checks to ensure data accuracy, consistency, and reliability.
  6. Collaboration and Communication: Work closely with stakeholders to gather requirements and ensure project alignment.
  7. Research and Development: Stay updated with technological trends and identify innovative solutions to address customer challenges.

Required Skills and Qualifications:

  1. Bachelor's or Master's degree in Engineering, Computer Science, or equivalent experience.
  2. At least 4+ years of relevant experience as a Data Engineer.
  3. Hands-on experience with cloud platforms such as AWS, Azure, or GCP, and familiarity with respective cloud services.
  4. Hands-on experience with one or more ETL tools such as Glue, Spark, Kafka, Informatica, DataStage, Talend, Azure Data Factory (ADF).
  5. Strong understanding of dimensional modeling techniques, including Star and Snowflake schemas.
  6. Experience in creating semantic models and reporting mapping documents.
  7. Solid concepts and experience in designing and developing ETL architectures.
  8. Strong understanding of RDBMS concepts and proficiency in SQL development.
  9. Proficiency in data modeling and mapping techniques.
  10. Experience integrating data from multiple sources.
  11. Experience working in distributed environments, including clustering and sharding.
  12. Knowledge of Big Data tools like Pig, Hive or NiFi would be a plus.
  13. Experience with Hadoop distributions like Cloudera or Hortonworks would be a plus.
  14. Excellent communication and presentation skills, both verbal and written.
  15. Ability to solve problems using a creative and logical approach.
  16. Self-motivated, analytical, detail-oriented, and organized, with a commitment to excellence.
  17. Experience in the financial services sector is a plus.


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