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Enterprise Data Infrastructure Manager
6 days ago
About Our Company Culture
We value collaboration, innovation, and customer satisfaction. We strive to create an inclusive environment where our employees can grow professionally and personally.
Job Summary:
This role is responsible for leading the implementation of data warehouse solutions that drive business decisions. As a Senior Data Engineer, you will design and develop scalable data pipeline solutions, manage and optimize the data lake on AWS, and establish data quality checks to ensure data accuracy, consistency, and reliability.
Key Responsibilities:
- Data Pipeline Development: Develop robust data pipelines capable of handling both structured and unstructured data effectively.
- Data Lake Management: Manage and optimize the data lake on AWS, ensuring efficient data storage, retrieval, and transformation.
- ETL Process Implementation: Implement efficient ETL processes, including low-latency data acquisition and stream processing using tools like Glue or Spark.
- Data Governance and Quality: Establish data quality checks to ensure data accuracy, consistency, and reliability.
- Collaboration and Communication: Work closely with stakeholders to gather requirements and ensure project alignment.
- Research and Development: Stay updated with technological trends and identify innovative solutions to address customer challenges.
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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