Senior Data/ML Engineer

4w1 month ago

Capstone Integrated Solutions

Remote · Full-time

About this role

Capnexus, a comprehensive build-as-a-service provider, is seeking a Senior Data/ML Engineer to lead data architecture, pipeline development, and integrations. This role applies advanced cloud data engineering skills on a platform leveraging generative AI to automate and modernize enterprise workflows.

Day-to-day responsibilities include designing multi-zone enterprise data lakes on Amazon S3, building batch and streaming ingestion pipelines using AWS Glue and Kinesis, and orchestrating transformations with Step Functions. You will also configure serverless querying via Athena and integrate QuickSight for analytics.

You will join a team of outstanding professionals highly experienced in retail software design and support. The culture is built on outcomes and delivery, with a repeatable business pattern applied across varied platforms and verticals.

This is an exciting opportunity to develop and deploy ML models on SageMaker for lead scoring and predictive maintenance, and to integrate Bedrock foundation models for generative AI capabilities like customer profile enrichment and hyper-personalization. You will lead data discovery workshops and migrate legacy systems to AWS.

Requirements

Experience with AWS services: Glue, Kinesis, Step Functions, Athena, SageMaker, Bedrock, Lake Formation, and DataSync
Expertise in data lake architecture and multi-zone design (raw, conformed, enriched, aggregated)
Proficiency in building batch and streaming data pipelines
Experience with ML model development and deployment using SageMaker
Knowledge of entity resolution, data deduplication, and Customer 360 data modeling
Familiarity with generative AI integration using foundation models like Amazon Bedrock
Ability to lead data discovery workshops and translate source system findings into architecture requirements
Experience with data security, governance, and migration from Azure to AWS

Responsibilities

Lead data architecture, pipeline development, and data integrations for a generative AI platform
Design and implement a multi-zone enterprise data lake on Amazon S3 with ingest, cleansing, and business layers
Build batch and streaming data ingestion pipelines using AWS Glue, Amazon Kinesis, and AWS Data Pipeline
Implement data transformation and orchestration frameworks using AWS Glue ETL and AWS Step Functions
Develop and deploy ML models on Amazon SageMaker for lead scoring, predictive maintenance, and audience segmentation
Integrate Amazon Bedrock foundation models for generative AI capabilities including customer profile enrichment and intelligent marketing automation
Design and implement entity resolution pipelines using Amazon Entity Resolution to create unified golden records
Implement data lake security using AWS Lake Formation, including row-level security and column-level encryption

Benefits

Opportunity to work with cutting-edge generative AI and cloud technologies on enterprise-scale data platforms
Culture built on outcomes and delivery with a focus on professional growth
Exposure to diverse platforms and verticals in the retail software industry