Senior Data Engineer

Our passion at EXL is enabling organizations to achieve a measurable, competitive advantage through Data Management. We partner with our clients to design and implement scalable, accessible, and innovative solutions. Our goal is to make sense of data to drive client’s business forward through data strategy, data governance and building cloud data platforms. EXL is a leading data analytics and digital operations and solutions company that partners with clients to improve business outcomes and unlock growth. By bringing together deep domain expertise with robust data, powerful analytics, cloud, artificial intelligence ("AI") and machine learning ("ML"), we create agile, scalable solutions and execute complex operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media, and retail, among others. Focused on driving faster decision-making and transforming operating models, EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect. Headquarters in New York, our team is over 44,500+ strong, with more than 50 offices spanning six continents. Location: Seattle, WA Employment Type: Full-Time (Hybrid) Responsibilities 6–12 years of experience in data engineering, platform engineering, or a closely related discipline. Streaming: Production experience with Kafka consumers and Flink stream processing — building, deploying, and operating streaming jobs at meaningful scale. GCP Data Stack: Strong SQL on BigQuery (or an equivalent cloud warehouse), with demonstrated query optimization, cost management, and partitioning chops. Python Data Engineering: Hands-on with Polars or Pandas at scale; deep working knowledge of Parquet partitioning and performance on large joins. ML Pipelines: Hands-on experience building and deploying components on Kubeflow Pipelines (KFP) and/or Vertex AI Pipelines; working proficiency with Docker. Event Store Design: Demonstrated experience designing event stores — partitioning by customer, time-ordered event assembly across sources, schema strategy for mixed event types (clicks, purchases, returns). Communication: Strong written and verbal communication; comfortable being the senior IC voice in design conversations with client stakeholders. Nice to Have Domain experience in Retail or E-commerce — customer journey data, transaction analytics, returns and exchanges modeling. Exposure to schema registry tooling (e.g., Confluent), Iceberg, or Delta Lake. Experience working in client-facing or consulting engagements. Google Cloud certifications (Professional Data Engineer or equivalent). #J-18808-Ljbffr EXL