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Senior Data Engineer (Machine Learning Enablement)

ByteBridge Technologies, Inc

Atlanta, Georgia • Today

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Contract

Depends on Experience

AWS Cloud Migration Lead

ByteBridge Technologies, Inc

Hybrid in Charlotte, North Carolina • 18d ago

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Contract, Third Party

Depends on Experience

Program Manager with Cloud Security & Vulnerability Management

ByteBridge Technologies, Inc

Hybrid in Quincy, Massachusetts • 27d ago

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Contract, Third Party

Depends on Experience

Workfront Developer

ByteBridge Technologies, Inc

Remote • 14d ago

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Contract

Depends on Experience

Data Center Technician Level 2

ByteBridge Technologies, Inc

Ashburn, Virginia • 13d ago

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Contract

Depends on Experience

ByteBridge Technologies, Inc

Job Details

Skills

Amazon Web Services
Code Review
Customer Relationship Management (CRM)
Data Migration
Data Science
Machine Learning (ML)
Google Cloud Platform

Summary

Role: Senior Data Engineer (Machine Learning Enablement)

Location: Atlanta, GA (Onsite occasionally to Midtown Atlanta client site)

Duration: 6 – 12 Months

Visa: GC

POSITION OVERVIEW

We are seeking a Senior Data Engineer with machine learning capabilities to build the scalable data foundation powering our ML models. You will lead the design of well-governed, cloud-native data platforms on Azure, bringing external retail and third-party data into a medallion architecture aligned to client master data. In this role, you will collaborate closely with Data Science and ML teams to set technical direction for data preparation and delivery.

DAY-TO-DAY RESPONSIBILITIES

Onboard and align external retailer and third-party datasets into a medallion architecture (bronze, silver, gold).
Profile retailer feeds to define partitioning strategies and address data gaps via imputation, mapping, or source blending.
Define and validate join keys against product, outlet, and customer dimension tables, resolving unmatched or duplicate keys.
Build and tune ETL/ELT data pipelines using Azure Data Factory, Azure Databricks, Azure Functions, and Synapse.
Execute large-scale data migrations—including multi-terabyte transactional volumes—with minimal to zero downtime.
Establish enterprise data quality controls, governance frameworks, and feature-ready models for recurring business cycles.
Partner with Data Science/ML teams to productionize models and maintain clear documentation and version control in GitHub.

REQUIRED SKILLS

Data Engineering Lead/Architect Experience: 7+ years building and managing production data platforms.
Azure Cloud Stack: 7+ years of hands-on experience with Azure Data Factory, Databricks, Functions, and Synapse.
Python & SQL: 7+ years of strong experience using PySpark or pandas for large-scale data transformation.
Architecture & Modeling: 7+ years of practical application of medallion architecture, dimensional modeling, and master data joins.

ADDITIONAL DESIRED SKILLS

Multi-Cloud Experience: AWS or Google Cloud Platform knowledge.
CRM Integration: Hands-on Salesforce integration (data sync, APIs, or migrations).
Domain Knowledge: Consumer goods or retail datasets (POS, syndicated data).
Machine Learning: Experience supporting ML feature pipelines and model productionization.

CANDIDATE PROFILE

The ideal candidate is an architectural-minded Senior Data Engineer who thrives at the intersection of enterprise data platforms and machine learning enablement. They possess strong technical leadership, deep expertise in Azure data ecosystems, and the communication skills necessary to bridge gaps between technical data science teams and business stakeholders.

Job Responsibilities

Design, build, and optimize scalable ETL/ELT data pipelines using Azure Data Factory, Databricks, Functions, and Synapse.
Profile and onboard external third-party/retail datasets into a medallion architecture (bronze, silver, gold) aligned with master dimension tables.
Execute large-scale data migrations and refactor complex semi-structured source data (e.g., XML) into analysis-ready structures.
Establish enterprise-wide data governance frameworks, quality controls, and feature-ready models to support recurring business cycles.
Partner with Data Science teams to productionize ML models while enforcing Git code review and documentation standards.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91173256
Position Id: 9111730
Posted 16 hours ago

Company Info

About ByteBridge Technologies, Inc

Bytebridge Technologies is a forward-thinking IT consulting and software development company committed to bridging the gap between innovation and business success. Our expertise lies in delivering cutting-edge solutions across software development, cloud services, automation, artificial intelligence, and IT infrastructure management.

At Bytebridge Technologies, we believe technology should empower businesses to achieve greater efficiency, scalability, and growth. Our team of seasoned professionals works closely with clients to understand their unique challenges and craft customized solutions that drive measurable results.

With a focus on quality, reliability, and innovation, we serve diverse industries, including finance, healthcare, retail, and more. Whether you're seeking to modernize legacy systems, automate workflows, or build future-ready applications, Bytebridge Technologies is your trusted partner on the digital transformation journey.

Fitment

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Ayush Acharya

Recruiter @ ByteBridge Technologies, Inc

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More jobs at ByteBridge Technologies, Inc in Atlanta, GA

ByteBridge Technologies, Inc

Job Details

Skills

Amazon Web Services
Code Review
Customer Relationship Management (CRM)
Data Migration
Data Science
Machine Learning (ML)
Google Cloud Platform

Summary

Role: Senior Data Engineer (Machine Learning Enablement)

Location: Atlanta, GA (Onsite occasionally to Midtown Atlanta client site)

Duration: 6 – 12 Months

Visa: GC

POSITION OVERVIEW

DAY-TO-DAY RESPONSIBILITIES

Onboard and align external retailer and third-party datasets into a medallion architecture (bronze, silver, gold).
Profile retailer feeds to define partitioning strategies and address data gaps via imputation, mapping, or source blending.
Define and validate join keys against product, outlet, and customer dimension tables, resolving unmatched or duplicate keys.
Build and tune ETL/ELT data pipelines using Azure Data Factory, Azure Databricks, Azure Functions, and Synapse.
Execute large-scale data migrations—including multi-terabyte transactional volumes—with minimal to zero downtime.
Establish enterprise data quality controls, governance frameworks, and feature-ready models for recurring business cycles.
Partner with Data Science/ML teams to productionize models and maintain clear documentation and version control in GitHub.

REQUIRED SKILLS

Data Engineering Lead/Architect Experience: 7+ years building and managing production data platforms.
Azure Cloud Stack: 7+ years of hands-on experience with Azure Data Factory, Databricks, Functions, and Synapse.
Python & SQL: 7+ years of strong experience using PySpark or pandas for large-scale data transformation.
Architecture & Modeling: 7+ years of practical application of medallion architecture, dimensional modeling, and master data joins.

ADDITIONAL DESIRED SKILLS

Multi-Cloud Experience: AWS or Google Cloud Platform knowledge.
CRM Integration: Hands-on Salesforce integration (data sync, APIs, or migrations).
Domain Knowledge: Consumer goods or retail datasets (POS, syndicated data).
Machine Learning: Experience supporting ML feature pipelines and model productionization.

CANDIDATE PROFILE

Job Responsibilities

Design, build, and optimize scalable ETL/ELT data pipelines using Azure Data Factory, Databricks, Functions, and Synapse.
Profile and onboard external third-party/retail datasets into a medallion architecture (bronze, silver, gold) aligned with master dimension tables.
Execute large-scale data migrations and refactor complex semi-structured source data (e.g., XML) into analysis-ready structures.
Establish enterprise-wide data governance frameworks, quality controls, and feature-ready models to support recurring business cycles.
Partner with Data Science teams to productionize ML models while enforcing Git code review and documentation standards.

Dice Id: 91173256
Position Id: 9111730
Posted 16 hours ago

Company Info

About ByteBridge Technologies, Inc

Fitment

Dice Job Match Score™

To see how well you match this job, please log in or create an account.

Once logged in, be sure to complete your profile to get the most accurate match score.

Contact the job poster

Ayush Acharya

Recruiter @ ByteBridge Technologies, Inc

View Profile

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

Similar Jobs

It looks like there aren't any Similar Jobs for this job yet.

Search all similar jobs

More jobs at ByteBridge Technologies, Inc in Atlanta, GA