Senior Data/ML Engineer (AWS)

Responsibilities

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• Participate in data discovery workshops to inventory source systems including property management platforms, marketing channels, and CRM data, and translate findings into data lake architecture requirements.
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• Design and implement a multi-zone enterprise data lake on Amazon S3 (raw, conformed, enriched, aggregated) with ingest, cleansing, and business layers aligned to the SOW architecture.
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• Build batch and streaming data ingestion pipelines using AWS Glue, Amazon Kinesis, and AWS Data Pipeline across CDP, marketing, and property management data sources.
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• Implement data transformation and orchestration frameworks using AWS Glue ETL and AWS Step Functions, including AWS Glue Data Catalog for metadata management and discovery.
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• Configure Amazon Athena for serverless SQL querying across the data lake; support QuickSight integration with curated data sets for business analytics.
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• Develop and deploy ML models on Amazon SageMaker for lead scoring, predictive maintenance, intelligent underwriting risk scoring, and AI-powered audience segmentation.
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• Integrate Amazon Bedrock foundation models to enable generative AI capabilities including customer profile enrichment, hyper-personalization, and intelligent marketing automation.
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• Use Kiro CLI to accelerate AI-assisted development workflows, spec-driven pipeline implementation, and automated code generation tasks.
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• Design and implement entity resolution pipelines using Amazon Entity Resolution to identify, deduplicate, and merge customer records into unified golden records.
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• Implement real-time and batch data synchronization pipelines between source systems and the Customer Data Platform (CDP).
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• Support Azure data lake migration: conduct discovery, assess schemas and transformation logic, provision AWS target environments, execute migration via AWS DataSync, and perform data validation and reconciliation.
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• Implement data lake security using AWS Lake Formation, including row-level security and column-level encryption.
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• Build and maintain data models to support Customer 360 views, ML feature stores, and executive analytics dashboards.
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• Ensure data quality, validation, and integrity across all pipeline stages and ML model outputs; support UAT for data-dependent features.
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• Collaborate with Full Stack, DevOps/MLOps, and AWS engagement teams; contribute to architecture documentation, pipeline runbooks, and data governance documentation.
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Requirements

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• 5+ years of data engineering or ML engineering experience, with at least 2+ years in AWS cloud environments.
• Strong proficiency in Python and SQL; experience with AWS data services including S3, Glue, Athena, Kinesis, and Step Functions.
• Hands-on experience with Amazon SageMaker for model development, training, tuning, and endpoint deployment.
• Working knowledge of Amazon Bedrock for integrating and applying foundation models in production-grade pipelines.
• Experience designing and implementing multi-zone data lake architectures on Amazon S3, including lifecycle policies and Lake Formation governance.
• Familiarity with Kiro CLI or comparable AI-assisted/agentic development tooling.
• Experience with entity resolution, deduplication, or master data management concepts and tools.
• Solid understanding of data modeling, feature engineering, data quality practices, and ML integration testing.
• Experience with AWS Lambda and AWS Step Functions for serverless workflow orchestration.
• Fami

Benefits

Additional Information

Capnexus is a comprehensive services provider. Our team consists of outstanding professionals, highly experienced in designing, building, and supporting retail software. We see ourselves as a build-as-a-service provider who follows a repeatable business pattern that can be applied to a variety of platforms and verticals. Having a culture built on outcomes and delivery at the core of the business, Capnexus is providing its customers with a complete suite of services for software development, system analysis, integration, implementation, and support, as well as the option to engage a single team to perform all the services they require. Who You Are and What You'll Do: Capnexus is looking for a highly skilled Senior AWS Data/ML Engineer to lead data architecture, pipeline development, and data integrations. This is an exciting opportunity to apply advanced cloud data engineering skills on a platform that leverages generative AI to automate and modernize enterprise workflows. _*]:min-w-0 gap-3">

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