Cloud Data Engineering Lead
4 days ago
ITI Data is seeking a highly skilled Cloud Data Engineering Lead to spearhead the design and development of scalable data pipelines on AWS. With a strong background in PySpark, Python, and AWS services, you will be responsible for building robust data integration solutions that enable data-driven insights across various internal and external sources.
This is an exceptional opportunity to join our team as a Cloud Data Engineering Lead where you will work closely with cross-functional teams to drive innovation and excellence in data engineering. As a key member of our data engineering team, you will have the chance to design, build, and deploy large-scale data pipelines using AWS Glue ETL jobs, Lambda functions, and other cloud-native services.
Key Responsibilities:
- Design, build, and unit test applications on Spark framework on Python, ensuring high-performance and scalability.
- Develop Python and PySpark-based applications to integrate data from relational databases (e.g., Oracle), NoSQL databases (e.g., DynamoDB, MongoDB), and filesystems (e.g., S3, HDFS).
- Build AWS Lambda functions on Python runtime, leveraging libraries such as pandas, json, boto3, requests, and avro.
- Create PySpark-based data pipeline jobs on AWS Glue ETL, requiring in-depth knowledge of AWS Glue Dynamic Frames and Options.
- Develop event-driven integration with Kafka Topics, utilizing Confluent Kafka libraries.
- Design and build generic, reusable utility applications in Python, optimizing performance for data access requirements.
- Configure S3 buckets, tiers, lifecycle policies, and strategic storage layers for
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