Job Description Summary:
As the Lead Data Engineer, you will be a technical lead for data products and subject matter expert to a team of data engineers. The successful candidate should be an analytical thinking, self-learner, and be able to lead a team through proactive solution development. If you have a passion for innovation, be at the forefront of our iconic digital transformation.
What You’ll Do for Us
- Design and develop scalable web applications using React, TypeScript/JavaScript, HTML, and CSS.
- Build backend services and REST APIs using technologies such as Java/Spring Boot, Python, .NET, or equivalent.
- Design and develop integrations among Salesforce, web and mobile applications, CRM platforms, databases, and enterprise systems.
- Work with relational databases such as SQL Server, including data modeling, queries, and application integration.
- Build secure API-driven solutions using modern authentication and authorization patterns.
- Data & Machine Learning Engineering
- Work with data from enterprise data platforms, customers, and external data providers to develop intelligent product capabilities.
- Develop data preparation, transformation, and feature engineering pipelines.
- Build predictive, classification, ranking, recommendation, segmentation, or forecasting models based on business requirements.
- Evaluate when to use traditional machine learning versus advanced techniques such as deep learning, transformers, computer vision, embeddings, vector search, or RAG.
- Develop batch or online model inference pipelines and services.
- Expose model predictions and recommendations through APIs for consumption by Salesforce, CRM, web, and mobile applications.
- Implement model and data validation, automated testing, and quality controls.
- Production Engineering & MLOps
- Build CI/CD pipelines for application and machine learning workloads.
- Support experiment tracking, model versioning, deployment, and lifecycle management.
- Monitor applications and models for availability, performance, data quality, and model degradation or drift.
- Support production solutions and troubleshoot issues across systems.
- Improve scalability, reliability, security, observability, and maintainability.
- Own capabilities throughout their lifecycle, from requirements through production support and continuous improvement.
Qualification & Requirements
- 5–10 years of professional software engineering experience, with experience spanning application development, data, or machine learning systems.
- Strong programming experience iat least one enterprise application development language such as Pyton, Java, C#, or equivalent.
- Strong experience with JavaScript/TypeScript and modern web development.
- Hands-on experience with React or a comparable modern frontend framework.
- Experience designing and developing REST APIs and backend services.
- Strong SQL skills and experience with relational databases such as SQL Server.
- Experience developing data pipelines, transforming datasets, and performing feature engineering.
- Practical experience developing machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or equivalent.
- Experience taking machine learning solutions beyond experimentation into production inference.
- Experience integrating multiple enterprise systems using APIs and modern integration patterns.
- Experience with automated testing, containers, monitoring, and production support.
- Strong software engineering fundamentals including modular design, testing, code reviews, debugging, and maintainability.
- Ability to work across Product, Data, Architecture, Business, and Engineering teams to translate requirements into production solutions.
- Experience using CI/CD tools – GitHub, GoCD, Terraform and/or Azure DevOps
- Solid knowledge about data modeling and architecture
- Knowledge with developing applications using public cloud, preferably Azure, specially focused in Data Services (CosmosDB, DynamoDB, Databricks, Glue, DataLake, Redshift, Azure Synapse etc.)
- Understand Agile Scrum, CI/CD, DevOps best practices
- Solid understanding of Git-based version control
What We Can Do For You
- Innovation & Technology: The ability to work with an award-winning team that is on the cutting edge of innovation.
- Exposure to World Class Leaders: Availability to global technology leaders that will expand your network and exposure you to emerging technologies and techniques.
- Agile Work Environment: We embrace agile with management that believes in removing barriers and empowering you to experiment, iterate and innovate.
Skills:
Agile, Azure Devops, Business Intelligence Software, DevOps, GitHub, Microsoft Azure, Non Relational Databases, Object-Oriented Programming (OOP), Python (Programming Language), Scala (Programming Language), Software Development, Software Engineering, Structured Query Language (SQL), Terraform (Software), Testing Methodology
Pay Range:
United States: 171,000 - 198,000 USD
Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:
15
Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Location(s):
United States of America
City/Cities:
Atlanta
Travel Required:
00% - 25%
Relocation Provided:
Yes
Job Posting End Date:
October 14, 2026
