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- 3+ years of Java development experience.
- 5+ years of experience with Big Data processing tools and frameworks such as Apache Spark, SparkSQL.
- Experience with Lakehouse technologies, such as Apache Hudi, Apache Iceberg, Databricks Delta Lake.
- Experience in building AI/ML pipelines.
- Deep technical understanding of ETL tools, low-latency data stores, multiple data warehouses and data catalogs.
- Familiarity with data testing and verification tooling and best practices.
- Experience with cloud services (AWS preferred, Google, Azure etc.).
- Proficient in working with Key-Value, Streaming, and Search Database technologies, including AWS DynamoDB, Apache Kafka, and ElasticSearch.
- Readiness to participate in the on-call rotation.
- Oversee the design, construction, testing, and maintenance of advanced, scalable data architectures and pipelines.
- Drive the development of innovative data solutions that meet complex business requirements.
- Create and enforce best practices for data architecture, ensuring scalability, reliability, and performance.
- Provide architectural guidance and mentorship to junior engineers.
- Tackle the most challenging technical issues and provide advanced troubleshooting support.
- Collaborate with senior leadership to align data engineering strategies with organizational goals.
- Participate in long-term planning for data infrastructure and analytics initiatives.
- Lead cross-functional projects, ensuring timely delivery and alignment with business objectives.
- Coordinate with product managers, analysts, and other stakeholders to define project requirements and scope.
- Continuously monitor and enhance the performance of data systems and pipelines.
AWSLeadershipDynamoDBElasticSearchETLJavaKafkaApache KafkaData engineeringElasticsearchSpark
Posted 2024-08-31
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