This is a fully remote position, open to applicants in United States.

📋 Description

• Create and develop consumable data assets (CDAs/data products) on the client's AWS data platform, which includes established schemas, documentation, and ownership.

• Transfer data assets to the designated product team.

• Collaborate with product engineering teams and platform users to establish data contracts, define domain ownership, and comprehend data in the broader context.

• Integrate bronze and silver layer data from existing data warehouses utilizing internal agentic tools.

• Develop tools to enhance the adoption of the data platform.

• Construct streaming and batch pipelines using Flink, SQL, Python, Kafka, Iceberg, and DynamoDB on AWS.

⛳️ Requirements

• Strong background in data engineering, particularly with large-scale data platforms and big data workloads.

• Practical experience in stream processing, event-driven architecture, and schema management.

• Significant streaming experience coupled with hands-on batch data engineering expertise.

• Familiarity with AWS as a user of a mature platform, with sufficient experience to establish streaming pipelines and batch jobs.

• Direct experience with Kafka, Iceberg, DynamoDB, and essential AWS services.

• Exposure to Apache Flink using SQL or Python (PyFlink), with the capacity to become productive within weeks without needing extensive specialization.

• Excellent stakeholder management and communication abilities.

• Proactive mindset when collaborating with other engineering teams and platform users.

• Capability to articulate the importance of data ownership and facilitate technical discussions from uncertainty to consensus.

• Experience at the Lead Engineer level, which includes defining technical direction, managing work end-to-end, and taking responsibility for outcomes rather than individual tasks.

• Proficient in English, both written and spoken.