Data Engineer
5 months ago
Job Responsibilities:
- Data Pipeline Development: Design, develop, and maintain efficient and reliable data pipelines to collect, process, and transform raw data from various sources into usable formats for analysis.
- Designing, implementing, and maintaining data pipelines that move data from various sources to the appropriate storage solution all while ensuring that the data is accurate, consistent, and secure.
- Develop and implement ETL (Extract, Transform, Load) processes to transform and aggregate data from multiple sources. Ensure data quality and consistency throughout the ETL process.
- Data validation and quality assurance: Assist in verifying migrated data's accuracy, completeness, and integrity through rigorous testing and quality assurance measures.
- Data extraction and transformation: to extract data from various sources, transform it as per project requirements, and load it into the new software system.
- Data mapping and documentation: Work closely with business stakeholders to understand data mapping requirements and document data structures, relationships, and business rules.
- Troubleshooting and issue resolution: Identify and resolve data-related issues during the migration process, collaborating with team members and other stakeholders as needed.
- Collaborative teamwork: Actively participate in team meetings and discussions, sharing insights, ideas, and progress updates related to the software migration project.
**Requirements**:
Job Requirements:
- Bachelor's degree in Computer Science, Data Science, Information Systems, or related field.
- 2-3 years of hands-on experience in data engineering, developing and maintaining data pipelines and ETL processes.
- Proficient in programming languages such as Python, Java, or Scala. Experience with ETL tools Apache Airflow and data integration technologies and solid understanding of database management systems (PostgreSQL, MySQL, NoSQL databases) and data modeling concepts.
- Experience working with cloud platforms such as AWS and Azure Cloud for data engineering tasks.
- Knowledge of data warehousing concepts and experience with tools like Amazon Redshift and Azure Synapse.
- Understanding of data management fundamentals, data modeling concepts, data integration techniques.
- Strong analytical and problem-solving skills with a keen eye for data accuracy and quality assurance.
- Willingness to learn new technologies, tools, and methodologies related to data engineering and software migration.
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