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Data Infrastructure Specialist
11 hours ago
**Job Overview:**
This role focuses on developing and implementing data warehouse solutions across the organization while managing large sets of structured and unstructured data.
The ideal candidate should have a solid understanding of data acquisition, integration, and transformation, with the ability to evaluate and recommend optimal architecture and approaches.
**Key Responsibilities:**
- Design robust data pipelines capable of handling both structured and unstructured data effectively.
- Create efficient data ingestion pipelines and ETL processes, including low-latency data acquisition and stream processing using tools like Kafka or Glue.
- Develop processes to integrate data warehouse solutions into operational IT environments.
- Manage and optimize the data lake on AWS, ensuring efficient data storage, retrieval, and transformation.
- Write, optimize, and maintain complex SQL queries and shell scripts to ensure efficient data processing.
- Continuously monitor system performance and recommend necessary configurations or infrastructure improvements.
- Prepare detailed documentation and present complete data workflows to teams.
- Develop and maintain data quality checks to ensure data in the lake and warehouse remains accurate, consistent, and reliable.
- Collaborate with cross-functional teams to gather requirements and ensure alignment with project goals.
- Scope and manage projects to ensure timely completion and successful outcomes.
**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.
- 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.
- Proficiency in 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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