Big Data Engineer
3 months ago
Key Responsibilities :
- Design and implement scalable and efficient data processing pipelines using Apache Spark and Java.
- Develop APIs and services for data ingestion, transformation, and aggregation to support analytics and machine learning models.
- Collaborate with data scientists, analysts, and cross-functional teams to understand data requirements and deliver innovative data solutions.
- Optimize Spark jobs for performance and cost efficiency across large datasets.
- Ensure high data quality and integrity by implementing robust testing and validation practices.
- Lead the adoption of best practices in code quality, CI/CD, and DevOps within the data engineering team.
- Mentor junior developers and contribute to knowledge sharing and team development.
Required Qualifications :
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- At least 7 years of software development experience, with a minimum of 5 years focused on big data processing using Apache Spark and Java.
- Proficient in Java programming and familiar with the Scala programming language.
- Strong experience in designing and implementing scalable data processing pipelines using Apache Spark and Java.
- Solid understanding of big data technologies and ecosystems (HDFS, YARN, Kafka, HBase, etc.).
- Experience with cloud platforms (AWS, Azure, or GCP) and understanding of cloud-native services for data processing.
- Familiarity with DevOps tools and practices, including Docker, Kubernetes, Jenkins, and Git.
- Excellent problem-solving skills, with the ability to tackle challenges in large-scale data environments.
- Strong communication and collaboration skills, with the ability to work effectively in a team and interface with technical and non-technical stakeholders.
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