We’re looking for a seasoned Principal Data Engineer to take ownership of modernizing our client's data systems and driving innovation across their platform. This role combines technical leadership with hands-on engineering, focused on building scalable, AWS-based data solutions that support advanced analytics, machine learning, and large language models. This is a direct-hire role with a hybrid work environment with a motivating work environment and inspiring leadership team.
Job Responsibilities
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Lead the redesign of data architecture to ensure scalability, cost efficiency, and readiness for AI/ML applications.
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Build and maintain real-time and batch data pipelines leveraging AWS services (e.g., Lambda, S3, DynamoDB).
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Develop reliable systems to prepare and serve high-quality data for ML and LLM use cases.
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Partner with product and engineering teams to deliver data solutions that meet business needs.
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Evaluate and adopt modern tools for data workflows, observability, and performance optimization.
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Champion best practices in data engineering and mentor team members.
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Oversee data quality, reliability, and security across the platform.
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Drive long-term data architecture strategy aligned with company growth and emerging AI demands.
Required Skills & Qualifications
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12+ years of experience in data engineering or related roles, with 2+ years in a senior/principal capacity.
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Proven track record designing and operating large-scale data lake or Lakehouse architectures on AWS.
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Strong understanding of distributed systems for data storage and processing.
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Hands-on experience preparing data for ML/AI pipelines.
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Proficiency in Python and Go for data-intensive systems.
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Expertise with DynamoDB and other AWS-native data services at scale.
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Strong communication skills and ability to lead cross-functional initiatives.
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Experience mentoring engineers and leading complex, multi-team projects.