Senior Manager, Software Engineer, Data Platform Segmentation

The Coca-Cola Company•Atlanta, GA

About The Position

The Senior Manager, Software Engineer Data Platform & Segmentation is a senior individual contributor accountable for the technical vision, design, and evolution of data platforms and segmentation capabilities that power Customer and Commercial product teams operating under a modern Product Operating Model. This role functions as a hands-on technical leader and multiplier, shaping how customer, commercial, and behavioral data is modeled, segmented, and activated across products enabling better decisions, personalization, and measurable business outcomes. The role emphasizes deep technical expertise, product partnership, and architectural leadership, rather than people management.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent experience.
8+ years of hands-on experience in data platform, analytics engineering, or backend engineering roles.
Deep expertise in data modeling, segmentation strategies, and large-scale data systems.
Strong experience with cloud-native data platforms and modern data tooling.
Proven ability to partner closely with product and business stakeholders.
Demonstrated impact as a senior individual contributor on complex, cross-team initiatives.

Responsibilities

Partner closely with Product Managers, Designers, and Tech Leads to co-own outcomes, not just data assets.
Participate actively in product discovery to ensure segmentation strategies are technically feasible, scalable, and analytically sound.
Translate business and customer questions into durable data models and segmentation frameworks.
Define and evolve the segmentation architecture across customer and commercial data domains.
Design scalable data models that support real-time, near real time, and batch segmentation use cases.
Ensure segmentation logic is reusable, explainable, and consistent across channels and products.
Make explicit trade-offs across latency, accuracy, cost, privacy, and maintainability.
Build and maintain high-quality, production-grade data pipelines and services.
Ensure strong standards for data quality, lineage, observability, and reliability.
Reduce fragmentation and duplication in segmentation logic across teams.
Leverage metrics to continuously improve data freshness, accuracy, and usability.
Act as a go-to expert for data platform and segmentation design.
Lead complex technical initiatives end-to-end through hands-on contribution.
Influence technical direction through design reviews, reference implementations, and documented standards.
Mentor senior engineers and Tech Leads through coaching and technical guidance (without direct management responsibility).
Demonstrate deep, hands-on expertise with Microsoft Azure data services and their application in large-scale, product-centric environments.
Design and evolve segmentation and data platform architectures leveraging Azure Data Fabric concepts, ensuring interoperability, governance, and reuse across domains.
Apply strong architectural judgment across core Azure data products, including data ingestion, storage, processing, analytics, and activation layers.
Optimize designs across cost, performance, latency, and scalability, using Azure-native capabilities and patterns.
Ensure secure-by-design implementations aligned with Azure identity, access, encryption, and compliance controls.
Partner with enterprise architecture, cloud, and security teams to ensure Azure data platform decisions align with broader enterprise strategy while preserving team autonomy.
Stay current on Azure data platform evolution and proactively assess new capabilities for business value, not novelty.
Serve as a trusted technical partner to Customer and Commercial stakeholders.
Communicate segmentation concepts, assumptions, and limitations in clear business language.
Proactively surface data constraints, privacy considerations, and trade-offs to enable informed decisions.
Support external partner and vendor conversations as a technical authority when needed.
Ensure segmentation approaches comply with data privacy, consent, and regulatory requirements.
Collaborate with Security, Privacy, and Legal teams to embed governance into platform design—not bolt it on later.
Advocate for responsible and ethical use of customer and commercial data.