
Data Engineer
13 hours ago
**Key Responsibilities**:
- Design, develop, and maintain scalable ETL pipelines for processing structured and unstructured data.
- Work extensively with **Apache Spark, Hadoop, Hive, Sqoop, Kafka, Talend**, and other big data technologies.
- Develop batch and streaming data processing workflows to support analytical and machine learning models.
- Build and optimize data lake and data warehouse solutions using **AWS services**like **S3, Glue, EMR, Redshift, Athena, Lambda**.
- Write high-quality, testable code in **Python, Scala, Java**, and **Shell scripting**.
- Collaborate with data scientists, analysts, and DevOps teams to support data initiatives and ensure optimal data delivery architecture.
- Troubleshoot and resolve data quality issues, performance bottlenecks, and ETL failures.
- Implement data governance and best practices for data security, privacy, and compliance.
**Technical Skills**:
- **Big Data & ETL Tools**:Apache Spark, Hadoop, Hive, Sqoop, Kafka, Talend
- **Programming Languages**:Python, Scala, Java, SQL, Shell Scripting
- **Cloud Platform**:AWS (S3, EMR, Glue, Redshift, Athena, Lambda)
- **Data Modeling & Warehousing**:Experience with schema design, star/snowflake schema, performance tuning
- **Machine Learning Platforms**:Exposure to ML model deployment and integration (experience with **ML Mode Bricks**or similar is a plus)
**Preferred Qualifications**:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
- Experience working in an agile environment.
- Strong analytical and problem-solving skills.
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