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Metro location and generalist title balanced by senior requirement and niche AWS/streaming requirements.
Low — core data engineering and cloud skills are broadly transferable across industries.
High — explicit 8–10 years plus mandatory AWS, streaming, and platform engineering expertise.
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Lead the design, development, and ownership of a greenfield data platform's data pipelines focusing on performance, scalability, and maintainability.
Embed AI throughout the data lifecycle and ensure data quality, integrity, and governance.
Manage, mentor, and review a team of data engineers; collaborate with cross-functional teams to translate business requirements into technical solutions.
8-10 years of experience in data engineering or data architecture roles.
Bachelor's degree in Computer Science, Information Systems, or related field; Master's degree is a plus.
Proficiency with AWS Data Services (S3, Glue, Athena, EMR, Kinesis).
Strong experience with data pipelines (batch and real-time), SQL, data lake/warehouse/lakehouse architectures, stream processing (Apache Flink, Kafka Streams, PySpark), and workflow orchestration (Apache Airflow).
Experienced in designing and operating scalable, cloud-based data engineering platforms with AI integration.
Demonstrates technical ownership and the ability to lead and mentor a data engineering team.
Comfortable working in fast-paced environments and translating complex business needs into robust, maintainable data solutions.
