
Data Engineer Professional
5 days ago
About ACE Money Transfer
We are a leading international money transfer service, dedicated to making cross-border payments fast, reliable, and affordable.
Job Description:
This role focuses on developing and implementing data warehouse solutions across the organization. As a Senior Data Engineer, you will be responsible for managing large sets of structured and unstructured data. You will analyze complex customer requirements, define data transformation rules, and oversee their implementation.
Key Responsibilities:
- Data Pipelines Design: Develop robust data pipelines capable of handling both structured and unstructured data effectively.
- Data Ingestion and ETL Processes Building: Create efficient data ingestion pipelines and ETL processes, including low-latency data acquisition and stream processing using tools like Kafka or Glue.
- Integration Procedures Development: Design and implement processes to integrate data warehouse solutions into operational IT environments.
- Data Lake Management: Manage and optimize the data lake on AWS, ensuring efficient data storage, retrieval, and transformation. Implement best practices for organizing and managing raw, processed, and curated data, with scalability and future growth in mind.
- SQL and Shell Script Optimization: Write, optimize, and maintain complex SQL queries and shell scripts to ensure efficient data processing.
- System Performance Monitoring and Optimization: Continuously monitor system performance and recommend necessary configurations or infrastructure improvements.
- Workflows Documentation and Presentation: Prepare detailed documentation, collaborate with cross-functional teams, present complete data workflows to teams, and maintain an up-to-date knowledge base.
- Governance & Quality: Develop and maintain data quality checks to ensure data in the lake and warehouse remains accurate, consistent, and reliable.
- Collaboration with Stakeholders: Work closely with CTO, PMOs, business and data analysts to gather requirements and ensure alignment with project goals.
- Project Scope and Management: Collaborate with project managers to scope projects, create detailed work breakdown structures, and conduct risk assessments.
- Research & Development (R&D): Keep up with the latest technological trends and identify innovative solutions to address customer challenges and company priorities.
Required Skills and Qualifications:
- Bachelor's or Master's degree in Engineering, Computer Science, or equivalent experience.
- At least 4+ years of relevant experience as a Data Engineer.
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP, and familiarity with respective cloud services.
- Hands-on experience with one or more ETL tools such as Glue, Spark, Kafka, Informatica, DataStage, Talend, Azure Data Factory (ADF).
- Strong understanding of dimensional modeling techniques, including Star and Snowflake schemas.
- Experience in creating semantic models and reporting mapping documents.
- Solid concepts and experience in designing and developing ETL architectures.
- Strong understanding of RDBMS concepts and proficiency in SQL development.
- Proficiency in data modeling and mapping techniques.
- Experience integrating data from multiple sources.
- Experience working in distributed environments, including clustering and sharding.
- Knowledge of Big Data tools like Pig, Hive or NiFi would be a plus.
- Experience with Hadoop distributions like Cloudera or Hortonworks would be a plus.
- Excellent communication and presentation skills, both verbal and written.
- Ability to solve problems using a creative and logical approach.
- Self-motivated, analytical, detail-oriented, and organized, with a commitment to excellence.
- Experience in the financial services sector is a plus.
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