Data Engineer - AWS/Big Data

Key Responsibilities

• Design, build, and optimize data pipelines and ETL processes using AWS Glue, Lambda, RDS, and S3.
• Develop scalable batch and streaming data processing workflows using Apache Spark, Spark Streaming, and Kafka.
• Work with SQL and NoSQL databases (MySQL, PostgreSQL, Elasticsearch) to design schemas and optimize queries for high performance.
• Write efficient and optimized SQL for data extraction, transformation, and analytics.
• Build and maintain data ingestion, transformation, and integration solutions across multiple systems.
• Collaborate with cross-functional teams (data science, analytics, engineering) to provide reliable, high-quality data.
• Use Scala, Java, and Python for data processing and automation scripts.
• Implement monitoring, logging, and alerting for data pipelines using AWS services (CloudWatch, CloudTrail).
• Ensure data security, compliance, and governance using AWS best practices.
  

Required Skills & Experience

• 5+ years of experience with AWS Services including RDS, AWS Lambda, AWS Glue, EMR, S3, and related big data technologies.
• 5+ years of experience working with Apache Spark, Spark Streaming, Kafka, and Hive.
• Strong experience in SQL and NoSQL databases (MySQL, PostgreSQL, Elasticsearch).
• Proficiency in Java and Scala, with hands-on scripting experience in Python and Unix/Linux shell.
• Deep understanding of Spark programming paradigms (batch and stream processing).
• Advanced knowledge of SQL, including query optimization, indexing, and performance tuning.
• Strong analytical and problem-solving skills with the ability to handle large datasets efficiently.