Sr.Software Engineer (Data) - People Tech

Are you passionate about Data Software Engineering and tackling complex batch and streaming data challenges? Do you aspire to revolutionize traditional data workflows with the power of GenAI? At Uber's PeopleTech Engineering Group, we are building the next generation of AI-powered data solutions with a GenAI-First mindset. Our mission is to transform people data workflows by seamlessly integrating GenAI at every possible stage of the process.

As a Senior Software Engineer (Data) - PeopleTech, you will lead Data Software Engineering across the entire lifecycle of People-Data within Uber's vast heterogeneous datasets and large-scale computing platform. This includes validating business concepts, designing and developing data pipelines, instrumenting GenAI in Data Workflows, Designing scalable Data Marts, Building MCP Servers and assisting the People Data Science team in deploying ML Models. At each step, you will leverage GenAI based tools and integrate GenAI wherever possible. You'll establish best practices, oversee data monitoring and operations, and collaborate closely with product and business teams to drive impactful outcomes. Additionally, you will provide quantitative support, market insights, and strategic recommendations to help partners make informed decisions. By driving innovation in rapidly evolving domains, you'll be at the forefront of advancements in data software engineering, and GenAI driven solutions.

What the Candidate Will Do

Design, develop, and deploy scalable, high performance data pipelines, ML Workflows, MCP Servers to analyze large datasets, generate insights that support data-informed decision-making.

Provide GenAI solutions to improve People-Data utilization productivity across data workflows and operations.

Develop solutions and tackle ambiguous problems by framing issues, generating hypotheses, and offering recommendations that blend software engineering , GenAI, analytics, and domain expertise.Perform analysis using relevant tools and provide strategic contributions that drive business improvements.

Document algorithms, methodologies, and findings thoroughly for transparency and reproducibility.

Collaborate with cross-functional teams to architect and execute technically rigorous Data and AI projects.

Mentor and support other engineers, share knowledge and best practices on building data tools around Gen AI and Machine LearningWork in a diverse, dynamic, collaborative, transparent, and inclusive environment where all ideas and opinions are valued.

Support on-call activities for critical issues.

Basic Qualifications

• 5 years of relevant work experience.
• Bachelor's degree in Computer Science, Statistics, Mathematics, Physics, Economics, Engineering, or a related quantitative field.
• 5+ years of coding and software development experience, with proficiency in Python (must), SQL (must), Java, GoLang or related languages.
• 3+ years of experience developing data services and data pipelines for business applications (-preferably using Apache Airflow or similar), with extensive hands-on experience in designing, building, evaluating, deploying, and monitoring data products end to end.
• 2+ years of Data Modeling experience for DataLakeHouse
• 2+ years of experience with data stream processing using Apache Flink and Kafka or similar.
• 1+ years of experience building Data Workflows/Systems utilizing GenAI/LLM Models
• 1+ years of experience working with unstructured data in Vector Databases
• Experience with databases, data warehousing, and ELT systems, including tools like Hadoop, Hive, Spark, Apache Airflow, Flink, Apache Kafka, GCP BigQuery, and Cloud Platforms (GCP, AWS).
• Experience in developing frameworks for common repetitive data processing patterns
• Experience in orchestrating Data Quality Frameworks, implementing Data Governance and Security with stringent access controls.
• Experience building monitoring jobs to detect Data Quality and Data Governance issues.
• Excellent written and verbal communication skills, with the ability to collaborate effectively in a distributed, cross-functional team environment.

• Proficient in Apache Airflow, Apache Flink, Kafka, Spark based data processing
• Proficient in GenAI Frameworks (ex: LangChain, LangGraph)
• Experience with AI Platforms like GCP VertexAI or similar
• Experience with Embedding Models and Vector Databases
• Experience with machine learning algorithms, including random forests, linear and logistic regressions, gradient boosting, classification, GANs, and anomaly detection techniques.
• Experience with API Development, gRPC
• Experience with CI/CD solutions in the context of MLOps and LLMOps, including automation with Infrastructure as Code (IaC) tools such as Terraform.
• Experience working with large-scale distributed systems and databases, particularly with very large datasets.
• Master Data Management experience