EXL is hiring a Senior Data Engineer to join a strategic AI / ML platform engagement with a leading specialty retailer. This is a hands-on build role embedded with the client's platform engineering team.
The role requires shipping production-grade data pipelines that feed real-time customer event data into machine learning workflows. The right person is comfortable owning the full lifecycle of pipeline design, build, and deployment: from streaming ingestion through event store design to model-ready feature delivery.
This is a high-visibility role with growth potential into a larger book of work as the engagement expands.
Salary Range: $93,900 - $154,200 annual base
The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.
Responsibilities- Design and operate event-driven data pipelines using Kafka consumers and Flink jobs to process high-volume customer events (clicks, purchases, returns) in near-real time.
- Build and optimize large-scale data transformations on Google Cloud Platform — BigQuery SQL, query performance tuning, and partitioning strategy at scale.
- Develop Python data engineering workloads using Polars or Pandas at scale, with rigorous attention to Parquet partitioning, join performance on large datasets, and memory efficiency.
- Build, deploy, and maintain ML pipeline components on Kubeflow Pipelines (KFP) and Vertex AI; package and deploy services with Docker.
- Design event store architecture: partitioning by customer, time-ordered event assembly across heterogeneous sources, and schema management for mixed event types.
- Partner with ML engineers, platform engineers, and data scientists to deliver clean, performant, model-ready data products.
- Document architecture decisions and contribute to engineering standards across the platform team.
- 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.
Skills Required
- 6-12 years of experience in data engineering, platform engineering, or closely related discipline.
- Production experience with Kafka consumers and Flink stream processing (building, deploying, operating streaming jobs).
- Strong SQL on BigQuery (or equivalent cloud warehouse) with query optimization, cost management, and partitioning.
- Hands-on Python data engineering with Polars or Pandas at scale; deep knowledge of Parquet partitioning and join performance.
- Hands-on experience building and deploying components on Kubeflow Pipelines (KFP) and/or Vertex AI Pipelines; working proficiency with Docker.
- Demonstrated experience designing event stores (customer partitioning, time-ordered event assembly, schema strategy for mixed event types).
- Strong written and verbal communication; able to serve as the senior individual-contributor voice with client stakeholders.
- Work on-site 3-4 days per week in Seattle, WA.
- Domain experience in Retail or E-commerce (customer journey, transaction analytics).
- 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).
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
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