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Team: Customer 360 Platform Location: Sterling, VA Focus: Python, SQL, Spark, applied statistics, machine learning, streaming, APIs About The Role Asurion is hiring a Senior Staff, Data Engineer for the Customer 360 Platform team. Customer 360 is a strategic platform that creates a trusted, intelligent view of our customers across products, partners, subscriptions, claims, service interactions, and digital experiences. This is a data engineering role with a strong data science foundation, on a team whose product is analytical data serving. The work goes beyond moving and transforming data: you will own the pipelines, statistical validation, models, and APIs that turn customer data into reliable metrics and predictions used in real business decisions, and you will serve those results to consuming applications through well-designed APIs and events. The role aligns to Asurion’s Senior Staff expectations for cross-team API design, domain data architecture, systems design, and technical leadership. What You Will Do Own analytical data products end to end, from data model and pipeline through to the metric, model, or API that a product or business decision depends on. Apply statistical methods in production work: experiment design and A/B testing, sample sizing and confidence intervals, significance testing, customer segmentation, and validation beyond basic null checks, including distribution and drift checks, anomaly detection, reconciliation, and outlier handling. Build, evaluate, and operate classical machine learning models in production (for example regression, gradient boosting, clustering, time series, and anomaly detection), including feature engineering, evaluation with metrics such as precision, recall, AUC, and MAPE, and monitoring for drift. Design and operate APIs, events, and data contracts that serve customer data to internal consumers, with clear schemas, versioning, and reliable latency. Build streaming and event-driven data flows using technologies such as Kafka, Kinesis, CDC, and Spark Structured Streaming to support near-real-time and operational analytics. Design customer data models for CustomerID, HouseholdID, profiles, subscriptions, interactions, relationships, identity resolution, lineage, confidence, and data quality, working across relational, NoSQL, graph, cache, search, and event-driven patterns. Partner with product, architecture, data, security, privacy, and analytics teams to drive scalable adoption of the platform. Mentor engineers and raise engineering and analytical standards across teams. Required Qualifications 10+ years of experience building APIs, backend services, and data-intensive platforms, with a track record of delivering measurable business or analytical outcomes such as attribution, fraud detection, churn reduction, conversion, or targeting. Solid grounding in applied statistics: sampling and sample sizing, confidence intervals, hypothesis testing, base rates, sources of bias in data, and evaluation of model quality. Hands-on experience taking classical machine learning models into production and owning them end to end, from features and training data through evaluation, serving, and drift monitoring. Strong Python and SQL, with production experience in Apache Spark. Experience building and operating APIs or backend services for data consumers, including API design, schema evolution, and production service architecture. Experience with event-driven architecture, data contracts, and streaming or messaging platforms such as Kafka, Kinesis, or Flink. Deep understanding of data modeling, database design, schema evolution, identity resolution, data quality, and source-of-truth patterns, across databases such as PostgreSQL, MySQL, DynamoDB, MongoDB, Redis, Elasticsearch/OpenSearch, Neo4j, or similar. Ability to influence multiple teams, shape technical direction, and drive cross-functional outcomes. Preferred Qualifications Experience with Databricks, Delta Lake, Unity Catalog, or Delta Live Tables. Experience with Node.js and TypeScript service development. Experience serving machine learning models at scale, with attention to latency and monitoring. Experience with Customer 360, customer data platforms, master data management, deterministic or probabilistic matching, confidence scoring, or graph-based models. Experience working in privacy-sensitive, regulated, multi-tenant, or client-segregated data environments. Is This Role Right for You? This role is a strong fit if you have built data platforms and also done the analysis: you think about whether a number can be trusted before you ship it, and your work carries through to the decision it informed. It is less of a fit if your recent experience is primarily platform operations (cluster administration, CI/CD, and pipeline monitoring) or generative AI application work without a foundation in classical statistics and modeling. Why Join Customer 360 Customer 360 is a high-impact platform where customer data, identity, confidence, privacy, statistics, and API design all matter. As a Senior Staff, Data Engineer, you will help define the data foundation, analytical standards, and serving layer for a platform that powers intelligence across Asurion. Equal Opportunity Asurion is proud to be an equal opportunity employer committed to building a diverse and inclusive workplace.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.