A Data Engineer at Apping Technology is responsible for designing, building, and maintaining the infrastructure that allows for the seamless flow, availability, and accessibility of data within the organization. This role ensures that data is collected, stored, and made accessible for analysis, enabling data-driven decision-making.
Key Responsibilities:
Develop and Maintain Data Pipelines: Design and implement scalable data pipelines that clean, transform, and aggregate data from various sources, ensuring efficient data processing and integration.
Ensure Data Quality and Integrity: Implement processes and systems to monitor data quality, ensuring production data is accurate and available for key stakeholders and business processes.
Collaborate with Data Science Teams: Work closely with data scientists to build complex algorithms and support machine learning initiatives, providing the necessary infrastructure and tools.
Optimize Data Systems: Identify, design, and implement internal process improvements, such as automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability.
Support Data Analytics Initiatives: Assist in building and maintaining the infrastructure required for optimal extraction, transformation, and loading (ETL) of data from various data sources.
Required Skills and Qualifications:
Educational Background: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
Programming Proficiency: Strong coding skills in programming languages such as Python and Java, which are essential for building and maintaining data infrastructure.
Database Management: Experience with both SQL and NoSQL databases, including MySQL, Oracle, PostgreSQL, and MongoDB, to handle diverse data storage needs.
Big Data Technologies: Familiarity with big data tools and frameworks like Hadoop, Spark, and Kafka, which are crucial for processing and managing large datasets.
Data Warehousing Solutions: Experience with data warehousing solutions such as Amazon Redshift, BigQuery, or Snowflake, enabling efficient data storage and retrieval.
Problem-Solving Skills: Strong analytical and problem-solving abilities to troubleshoot data-related issues and drive continuous improvement.
Communication Skills: Effective communication skills to collaborate with cross-functional teams and convey complex technical concepts to non-technical stakeholders.
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