Data Engineer

Who we are Who we are.Reality Defender is an award-winning cybersecurity company helping enterprises and governments detect deepfakes and AI-generated media. Utilizing a patented multi-model approach, Reality Defender is robust against the bleeding edge of generative platforms producing video, audio, imagery, and text media. Reality Defender's API-first deepfake detection platform empowers teams and developers alike to identify fraud, disinformation campaigns, and harmful deepfakes in real time.Backed by world class investors including DCVC, Illuminate Financial, Y Combinator, Booz Allen Hamilton, IBM, Accenture, Rackhouse, and Argon VC, Reality Defender works with leading enterprise clients, financial institutions, and governments in order to ensure AI-generated media is not used for malicious purposes. Data Engineer Role Youre looking for a Data Engineer who can build and scale the infrastructure powering our data platform, with a strong foundation in distributed systems and cloud-native tooling. You’ll design and operate the pipelines that move, process, and prepare multi-terabyte and streaming datasets — including audio and video — for Reality Defender’s detection models, and you’ll work closely with ML engineers and researchers to keep that data flowing reliably at scale. Responsibilities Design, build, and operate large-scale data processing pipelines handling multi-terabyte and streaming datasets, including audio/video transcoding, feature extraction, and preprocessing workflows. Deploy, scale, and troubleshoot containerized workloads on Kubernetes and AWS in production environments. Build and maintain distributed data processing jobs using frameworks such as Spark and Ray. Design and operate workflow orchestration systems (e.g., Airflow) with dependency management, retries, monitoring, and alerting for production pipelines. Administer and tune enterprise databases, including performance tuning, backup/recovery, access control, and scaling strategies. Partner with ML engineers and researchers to support training pipelines, model retraining triggers, feature stores, and other MLOps workflows. Who you are Hands-on experience with Kubernetes and AWS, including deploying, scaling, and troubleshooting containerized workloads in production environments. Proficiency with high-performance/distributed computing frameworks such as Spark and Ray for processing large-scale datasets. Experience with workflow orchestration tools such as Airflow (or comparable systems like Dagster, Prefect, or Luigi) to schedule and manage complex data pipelines. Strong programming skills in Python and SQL; experience with Golang is a plus. Demonstrated track record building and operating large-scale data processing pipelines, ideally handling multi-terabyte or streaming datasets. Experience working with audio or video data at scale is a strong plus (e.g., transcoding, feature extraction, or preprocessing pipelines). Familiarity with common data transformation patterns applied to large datasets (ETL/ELT, batch and stream processing, data validation and quality checks). Experience designing and maintaining job orchestration systems, including dependency management, retries, monitoring, and alerting for production pipelines. Bonus experience orchestrating machine learning workflows (training pipelines, model retraining triggers, feature stores, or MLOps tooling). What we offer Healthcare plans with 100% premium coverage for employees and partial coverage available for dependents Dental and Vision plans with 100% premium coverage for employees and their dependents Short/Long-term disability and life insurance plans with 100% premium coverage for employees FSA/HSA and 401k programs Equity compensation 20 days of PTO per year 12 weeks of Parental Leave Learning and Development budget Monthly wellness benefits Annual company-sponsored offsite HQ in NYC Benefits Daily in-office lunch through UberEats Commuter benefits Remote Fridays Happy Hours and other local events #J-18808-Ljbffr