Big Data Engineer
3 weeks ago
Key Responsibilities :
Data Pipeline Development :
- Design, develop, and maintain scalable data pipelines using Big Data technologies (e.g., Apache Hadoop, Apache Spark, Kafka).
- Implement data ingestion strategies to efficiently load and transform large datasets from various sources.
Data Architecture and Modeling :
- Collaborate with data architects to design and optimize data models that support analytical workloads.
- Create and maintain data schemas, ensuring efficient storage and retrieval of data across multiple platforms.
ETL Development :
- Develop ETL processes to extract, transform, and load data into data lakes and warehouses.
- Utilize tools like Apache NiFi, Talend, or custom-built solutions to automate data workflows.
Performance Tuning :
- Monitor and optimize the performance of data processing jobs to ensure high availability and reliability.
- Identify bottlenecks in data processing and implement solutions to improve efficiency.
Data Quality and Governance :
- Establish data quality frameworks to ensure accuracy, consistency, and reliability of data.
- Implement data governance practices, including metadata management and compliance with data regulations.
Collaboration and Stakeholder Engagement :
- Work closely with data scientists, analysts, and business stakeholders to understand data requirements and translate them into technical specifications.
Participate in cross-functional teams to develop data-driven solutions that support business objectives.
Troubleshooting and Support :
- Provide ongoing support for data systems, troubleshooting issues, and implementing fixes as necessary.
- Develop monitoring tools and dashboards to ensure data pipeline health and performance.
Documentation and Knowledge Sharing :
- Maintain thorough documentation of data processes, architectures, and standards for future reference.
- Share knowledge and best practices with team members through training sessions and collaborative discussions.
Continuous Improvement :
- Stay current with industry trends and emerging technologies in the Big Data landscape.
- Propose and implement enhancements to existing data solutions and practices.
Mentorship and Leadership :
- Mentor junior team members, providing guidance on technical challenges and career development.
- Lead initiatives to improve team processes and efficienc
- Document processes, data flows, and system architecture for future reference.
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