
Data Engineer
2 days ago
Responsibilities:
Design and implement robust ETL/ELT pipelines for data ingestion, transformation, and storage.
Optimize data workflows to ensure scalability and performance.
Integrate data from multiple sources into centralized data platforms.
Design and maintain databases, data lakes, and warehouses for structured and unstructured data.
Ensure data accuracy, consistency, and completeness through monitoring and validation.
Implement data security and compliance measures in line with industry regulations.
Work with data analysts, AI engineers, and other stakeholders to define data requirements.
Provide technical support for analytics and reporting tools.
Evaluate and adopt new technologies for improving data architecture and performance.
Document processes and maintain up-to-date technical guides.
Qualifications and Skills Required:
Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
4 to 6 years of experience required.
Proven experience in building and managing data pipelines and architectures.
Strong knowledge of databases (SQL and NoSQL), data modeling, and schema design.
Proficiency in data processing tools and frameworks (e.g., Apache Spark, Hadoop).
Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
Proficiency in programming languages such as Python, Scala, or Java.
Preferred
Experience with data visualization tools like Power BI or Tableau.
Familiarity with real-time data processing technologies (e.g., Kafka, Flink).
Certifications in cloud data services (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate).
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