Note: The job is a remote job and is open to candidates in USA. IS3 Solutions is seeking a Data Engineer, GenAI Data Systems professional to build and operate reliable data systems supporting large-scale datasets and annotation workflows. The role focuses on data modeling, ETL and ELT pipelines, Databricks workloads, dashboards, telemetry, automation, and cross-functional delivery across the full lifecycle of data solutions.

Responsibilities

• Build and maintain data pipelines and processing frameworks supporting dataset creation, annotation workflows, and large scale data movement across batch and incremental processing patterns
• Design and maintain data models and pipelines for large scale multimodal datasets including text, image, video, and audio
• Design and support high volume logging and telemetry systems with a focus on operational efficiency, monitoring, and troubleshooting
• Develop and maintain dashboards, reports, metrics, and alerting solutions that track throughput, quality, cost, and overall program health
• Design and maintain data models, schemas, databases, lakehouse environments, dimensional models, and reporting structures
• Build, optimize, and support Databricks workloads including transformations, orchestration, governance, and performance tuning
• Implement data quality validation, monitoring, and alerting mechanisms to improve reliability and trust in data assets
• Develop and maintain workflows that move data into and out of annotation platforms including preprocessing, post processing, validation, and delivery of annotated datasets
• Support engineering needs related to annotation project user interfaces, testing activities, and quality assurance initiatives
• Develop backend services, automation tools, and production software using Python and established engineering best practices
• Troubleshoot complex technical issues spanning multiple systems and identify root causes to implement sustainable solutions
• Partner with business, engineering, and operational teams to gather requirements, communicate progress, and document systems and procedures
• Independently evaluate ambiguous requests, design solutions, manage priorities, and execute cross functional initiatives
• Integrate pipelines and applications with cloud platforms, storage systems, and data annotation technologies while ensuring strong observability and reliability

Skills

• • Bachelor's Degree in Computer Science, Engineering, or a related field, or equivalent professional experience
• • Four or more years of professional experience in Data Engineering or a related technical discipline
• • Proven experience designing, building, and operating production ETL and ELT pipelines supporting large and complex datasets
• • Strong proficiency in SQL and Python
• • Experience with version control systems, testing frameworks, and continuous integration and continuous deployment practices
• • Experience with workflow orchestration tools such as Airflow, Dagster, Databricks Jobs, or similar platforms
• • Experience designing and maintaining data models, databases, warehouses, or lakehouse architectures
• • Experience supporting high volume logging or telemetry solutions
• • Experience building dashboards, reports, metrics, and alerting solutions
• • Hands on experience with Databricks, Spark, Delta Lake, or similar large scale data platforms
• • Experience working with AWS, Azure, or Google Cloud Platform
• • Demonstrated proficiency using AI tools for coding and data related workflows while applying strong engineering fundamentals and technical judgment
• • Strong problem solving and troubleshooting skills
• • Excellent written and verbal communication skills
• • Ability to work independently, manage competing priorities, and proactively communicate status and risks
• • Eight or more years of Data Engineering or Analytics Engineering experience
• • Experience supporting human in the loop annotation programs and data labeling workflows
• • Direct experience with SuperAnnotate
• • Experience supporting machine learning, Large Language Model, or Vision Language Model training data pipelines
• • Experience working with large scale multimodal datasets including text, image, video, and audio
• • Experience with JavaScript, TypeScript, HTML, or full stack application development supporting internal tools and workflow applications

Benefits

• Remote and onsite work models

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