Sr Data Engineer

Lead the design and development of complex data pipelines for data collection and processing. Develop and maintain advanced data storage solutions. Ensure data quality and consistency through sophisticated validation and cleansing processes. Implement advanced data transformation techniques to prepare data for analysis. Collaborate with cross-functional teams to understand data requirements and provide innovative solutions. Optimize data engineering processes for performance, scalability, and reliability. Design, develop, and maintain enterprise-class data pipelines capable of processing billions of records daily with high throughput and reliability Write advanced, complex SQL queries for data transformation, analysis, and optimization across petabyte-scale datasets Build and optimize both batch and real-time/streaming data systems that solve low-latency business problems Hands-on development of scalable data architectures in GCP using BigQuery, Bigtable, Dataproc, and Pub/Sub Perform deep data analysis to identify trends, anomalies, and insights that drive business decisions Ramp up on Agentic AI capabilities and apply outside-the-box thinking to conceptualize innovative data solutions Troubleshoot and resolve complex data pipeline issues, performing root cause analysis and implementing fixes Optimize query performance, data models, and pipeline efficiency to meet strict SLAs Actively engage in design and code reviews, maintaining high standards of code quality and engineering excellence Ramp up quickly on existing data systems, codebases, and business context to start delivering value immediately Take ownership of end-to-end data pipeline development from design through production deployment Explore and apply Agentic AI approaches to enhance data engineering workflows and solutions Implement data quality checks, monitoring, and alerting for production pipelines Collaborate with Product, Analytics, and Engineering teams to understand data requirements and deliver solutions Participate in on-call rotations and respond to production incidents with urgency Document technical designs, data flows, and operational runbooks Contribute to continuous improvement of data engineering practices and standards 3+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience Demonstrated deep hands-on experience building enterprise-class data platforms and pipelines at scale Expert-level SQL skills - ability to write and optimize complex queries across large datasets (billions of records) Strong experience with both batch processing (Spark, Dataproc) and real-time/streaming systems (Kafka, Pub/Sub, Dataflow) Proven ability to build low-latency data systems that solve time-sensitive business problems Hands-on proficiency with Cloud data services. Preferably - BigQuery, Bigtable, Dataproc, Cloud Storage, Pub/Sub Strong Python programming skills for data pipeline development and automation Experience with workflow orchestration tools (Airflow, UC4, or similar) Solid understanding of data modeling, schema design, and data warehouse concepts Experience with CI/CD pipelines and DevOps practices for data systems Strong debugging and troubleshooting skills for distributed data systems Ability to work in a fast-paced environment and ramp up quickly on new technologies and domains Experience with Agentic AI - ability to conceptualize and design data solutions leveraging Agentic AI with outside-the-box thinking Experience in Marketing Technology (MarTech) or Advertising Technology (AdTech) domain Experience with Customer Segmentation and Activation across owned and paid channels Experience with real-time integration with third-party AdTech platforms Familiarity with AI/ML pipelines or AI-enhanced data systems Bachelor's degree in Computer Science, Engineering, or related technical field