Senior Data Scientist to design and build scalable data platforms, pipelines, and cloud solutions that power global pricing decisions.
Compensation
Pay for performance -Annual incentive Bonus plan.
Responsibilities
Build infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability
Perform debugging, troubleshooting, modifications and testing of integration solutions
Operationalize the developed jobs, processes and models
Create databases and infrastructure to process data at scale
Lead data engineering initiatives, design and implement data pipelines, and drive strategic direction of the data engineering practice at Capital One.
Locations (2)
McLean, Virginia, United States
Richmond, Virginia, United States
Compensation
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $269,100 - $307,200 for Staff Data Engineer Richmond, VA: $244,700 - $279,200 for Staff Data Engineer
Responsibilities
Build awareness, increase knowledge and drive adoption of modern technologies
Promote a culture of engineering excellence
Effectively communicate with and influence key stakeholders across the enterprise
Operate as a trusted advisor for a specific technology, platform or capability domain
Lead the way in creating next-generation talent for Tech
WB Games Data Engineering Co-op: Needham, MA - January-May 2027
The CTS Data Engineering team is developing data solution at scale to support game telemetry pipelines, 3rd party data ingestion and Consent management solution using the Databricks platform.
Compensation
Pay Rate: $31 per hour USD for undergrad interns.
Responsibilities
Support build up for Databricks Semantic layer
Consolidate DataDog observability into one CTS platform repository for better cross-team collab and management
Work on data solution at scale to support game telemetry pipelines, 3rd party data ingestion and and Consent management solution
The Data Quality Expert works with IT and business stakeholders to facilitate the creation, maintenance, and validation of strategic data assets. This role supports the definition and deployment of data quality and observability practices, defines measures and KPIs and implements rules needed to verify and validate the quality and fitness of the enterprise data.
Responsibilities
Consult and advise the business with regard to data quality
Partner closely with data creators, data stewards, data consumers, and different IT teams to ensure data is usable, timely, robust, trustworthy, and compliant
Look at the end-to-end data flow and lifecycle, from generation/acquisition to exploitation and value, to establish data quality dimensions, rules, and indicators
Apply data quality principles and best practices to design and maintain policies, methodologies, guidelines around data quality, data profiling, data cleansing, including KPI/metrics definitions
Collaborate with business stakeholders to identify attributes that require data quality and corresponding business rules
Requirements
Bachelor/Master degree in Computer Science or related fields
Define and execute the multi‑year architecture, semantic layer, and delivery strategy for customer data across Questrade, leading a high‑performing technical team while remaining hands‑on.
Compensation
Base salary range: $170,000 - $200,000. The final compensation package will be commensurate with the successful candidate's experience, skills, and geographic location (Canada). It includes a comprehensive benefits plan and a competitive incentive (bonus) program for Full-Time Permanent roles.
Responsibilities
Set the multi‑year customer data architecture and analytics engineering vision
Architect and maintain the enterprise semantic layer
Define, champion, and enforce software engineering best practices within analytics
Direct complex, greenfield implementations and critical data transformations
Implement strict data governance, cost optimization, data observability, and access controls
Requirements
Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or equivalent practical experience
Nice to have: modern AI coding agents (Claude Code)
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