What are the responsibilities and job description for the Data Engineer position at Purchasing Power?
Work at Purchasing Power
Position: Data Engineer
Location: Atlanta/Hybrid work model
Who Are We: Purchasing Power (corp.purchasingpower.com)
We are an Atlanta-based voluntary benefit company offering an industry-leading employee purchase program for brand-name consumer products, online education services and travel offerings through convenient payroll deduction, helping employees achieve financial flexibility.
The Opportunity: The Data Engineer will build, scale, and optimize real-time data systems and pipelines using Apache Kafka (Confluent), AWS, and a modern data stack. Work hands-on with streaming, ETL, distributed infrastructure, and PostgreSQL to fuel analytics and product innovation while deploying AI/ML frameworks, agentic automation, and MLOps tools to enable powerful analytics, advanced modeling, and a responsive data infrastructure.
What You Will Do:
- Architect and build real-time streaming pipelines with Kafka, Confluent Schema Registry, and Zookeeper, ensuring scalable, event-driven data platforms
- Leverage AWS services: build and manage ETL/ELT workflows on Glue and EMR, deploy scalable workloads using EC2, and orchestrate storage in S3
- Optimize and maintain PostgreSQL and other databases: schema design, advanced SQL, and performance tuning
- Integrate AI/ML tools and frameworks (TensorFlow, PyTorch, Hugging Face) into data workflows; design pipelines to prepare and serve data for training and inference
- Automate data quality checks, feature extraction, and anomaly detection using AI-powered data validation and observability tools
- Collaborate with ML engineers to deploy, monitor, and continuously improve machine learning models within production data pipelines (batch and real-time), leveraging MLOps platforms (e.g., MLflow, SageMaker, Airflow, Kubeflow)
- Experiment with vector databases and retrieval-augmented generation (RAG) pipelines to support LLM and GenAI initiatives
- Build and optimize event-driven and cloud-native architectures, supporting scalable, reliable AI data products
The Experience You Will Bring:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical field
- 3 years of Data Engineering experience with hands-on Kafka (Confluent/OSS) and AWS experience
- Hands-on with automated data quality, monitoring, and observability tools for AI/data workflows
- Advanced SQL and strong database fundamentals in PostgreSQL and other traditional and No-SQL databases
- Proficiency in either Python, Scala, or Java for workflow development and AI integrations
- Proficient with synthetic data generation, vector stores, or GenAI data products
- Experience integrating ML models into data pipelines, using frameworks like PyTorch, TensorFlow, and MLOps platforms (Airflow, MLflow, SageMaker, Kubeflow)
Your Well Being:
- Hybrid work model (Onsite/Offsite)
- Comprehensive benefits: medical, dental, vision, company paid Basic Life/AD&D
- 401k Retirement Plan
- Flexible PTO
- Career Development
- Employee Purchase Program
What We Stand For:
- We act with intensity, urgency and a passion for supporting our customers and growing our business. We strive for excellence.
- We hold ourselves accountable and expect it of each other. We attack problems with a positive “can do” attitude. We do what we say we’ll do.
- We deliver as one team, working together with integrity, respect, trust, transparency, and fun. We are better because we work here.
- We believe our unique diversity and authenticity make us a better company, allows us to be our best selves and is a competitive advantage.
- We exhibit innate curiosity and creativity to innovate and reimagine how things can be done. We ask, is there a better way?
Purchasing Power is an equal opportunity employer. At Purchasing Power, we make all employment decisions, which include hiring, promoting, transferring, demoting, evaluating, compensating and separating, without regard to sex, sexual orientation, gender identity, race, color, religion, age, national origin, pregnancy, citizenship, disability, service in the uniform services, or any other classification protected by federal, state or local law.