Senior Data Engineer

Qualifications

• Required Skills & Experience Nice to Have Work Arrangement & Eligibility
• 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.
• 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).
• This role requires 3–4 days per week onsite in Seattle, WA. Fully remote and out-of-state candidates will not be considered.
• EXL is open to sponsoring H1B transfers for qualified candidates.
• Required Skills & Experience - 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). Work Arrangement & Eligibility - This role requires 3–4 days per week onsite in Seattle, WA. Fully remote and out-of-state candidates will not be considered. - EXL is open to sponsoring H1B transfers for qualified candidates.