Richmond, VA

Data Jobs in Richmond, VA

5 jobs found

Include remote jobs

5d ago

Lead Data Engineer (Finance Tech)

Capital One Richmond, VA

Richmond, VA

5d ago

$179k - $205k/yr Full time Big Data Bigdata Cloud Architecture

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Job Description

The Lead Data Engineer role in Capital One's Finance Tech group focuses on designing, building, testing, implementing, and supporting data engineering solutions, delivering cloud-based data platforms via Agile teams to empower financial decision-making.

Responsibilities

Partner with cross-functional Agile teams to design, build, test, deploy, and support technical solutions across full‑stack development tools and technologies
Collaborate with developers who specialize in machine learning, distributed microservices, and full‑stack systems
Work with Java, Scala, and Python, plus open source RDBMS and NoSQL databases, and cloud data warehouses such as Redshift and Snowflake
Share enthusiasm for emerging technologies, experiment with new tools, participate in internal and external tech communities, and mentor other engineers
Collaborate with digital product managers to deliver robust cloud based solutions that enable financial empowerment for millions
Perform unit tests and participate in code reviews to ensure designs are solid, code is clean, and performance is tuned

Requirements

Bachelor’s Degree
Minimum 4 years of experience in application development (internships do not count)
Minimum 2 years of experience with big data technologies
At least 1 year of cloud computing experience (AWS, Microsoft Azure, or Google Cloud)

Technologies

Java
Scala
Python
Redshift
Snowflake
MongoDB
Cassandra
Hadoop
Hive
MapReduce
EMR
Kafka
Spark
Gurobi
MySQL
UNIX/Linux
Shell scripting
AWS
Microsoft Azure
Google Cloud

Benefits

Health benefits
Financial benefits
Performance-based incentive compensation including cash bonuses and long-term incentives

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7d ago

Data Engineer, Finance Data & BI

MCKESSON Richmond, VA

Richmond, VA

7d ago

$107k - $178k/yr Full time Analytics Business Intelligence Cloud

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Job Description

McKesson is seeking a Data Engineer on the Finance Solutions team to design, build, and maintain scalable data pipelines and analytics-ready datasets for Finance Data & BI in a hybrid Richmond, VA role.

Responsibilities

Tackle complex problems across the full data stack, from advanced data wrangling (SQL, Python, Spark, or similar) to delivering stakeholder-ready, production-scale data solutions
Architect new designs and reengineer existing ones, optimizing data structures, relational databases, and database code
Build, test, and maintain robust, scalable ETL/ELT pipelines using modern cloud technologies that support advanced analytics and AI/ML workloads
Develop and maintain database code, including stored procedures, functions, and performance-optimized transformations
Create and sustain ETL processes and contribute to CI/CD deployment workflows using GitHub Actions or similar tools
Implement and optimize data models, including dimensional modeling, within the Finance data environment
Optimize data architecture for performance, scalability, and cost efficiency across large financial datasets
Design automated data quality checks, anomaly detection, and validation processes to ensure accuracy for downstream analytics and AI use cases
Ensure all data solutions meet governance and compliance standards, including SOX requirements
Collaborate with Finance teams (Accounting, FP&A), BI, and Data Product partners to translate complex business needs into scalable technical solutions
Communicate technical concepts clearly to non-technical stakeholders, balancing innovation with operational risk and controls
Enable trusted data environments required for forecasting models, scenario planning, and AI-driven insights
Contribute to the strategic evolution of the Finance data platform by evaluating and piloting emerging tools and technologies

Requirements

4+ years of relevant experience as a Data Engineer
4+ years of hands-on experience with data warehouse solutions, cloud platforms, relational databases, and data visualization or dashboarding tools
4+ years of experience working with structured and unstructured data in batch and real-time data processing environments
Strong proficiency in object-oriented programming languages such as Python, Java, or C#
Demonstrated experience with Google Cloud Platform (GCP) preferred over other platforms (e.g., Snowflake, Databricks, Microsoft, Teradata)
Proven enterprise experience including:
- Building and optimizing cloud-based data solutions
- Supporting business-critical systems
- Designing or supporting production-scale AI/ML data pipelines
- Embedding data governance by design
- Data warehousing and ETL best practices
- CI/CD and version control using GitHub

Technologies

SQL
Python
Spark
Google Cloud Platform (GCP)
GitHub Actions
GitHub
Matillion
PySpark
Oracle JD Edwards
Snowflake
Databricks
Teradata
Java
C#

Benefits

Base pay range: USD 106,500 - 177,500 per yearly
Annual bonus or long-term incentive opportunities may be offered

Hybrid expectations

This position is based in Richmond, VA with 3 to 5 days in the office each month
Preferred candidates must currently reside within a reasonable commuting distance (defined as within 60 miles of Richmond)
Relocation assistance is not available for this role

Compensation

Base: $130,000 to $140,000
10% Annual Incentive

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10d ago

Lead Data Engineer - Data Transformation (Modeling and Architecture)

Capital One Richmond, VA

Richmond, VA

10d ago

$179k - $205k/yr Full time Data Architecture Data Engineer Data Governance

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Job Description

Capital One is seeking a Lead Data Engineer focused on data transformation, modeling, and architecture. The role centers on designing scalable data models, enforcing governance, and delivering AI-ready architectures across Data Lake and Data Warehouse environments on cloud platforms.

Responsibilities

Develop and maintain comprehensive data models across conceptual, logical, and physical layers to support scalable architectures and strong data integrity across enterprise systems.
Lead the design of the organization's data landscape by applying Consumer Driven design principles, ensuring data structures reflect business realities and evolving needs.
Architect and implement robust data ecosystem solutions, including Data Lake and Data Warehouse patterns, to meet diverse analytical and operational requirements.
Support high performance data pipelines and complex transformations using SQL, Spark, and Python to process large-scale datasets efficiently.
Define and enforce rigorous data governance standards while managing metadata frameworks to ensure data compliance and discoverability.
Translate complex technical concepts into actionable business insights and independently lead initiatives while collaborating with stakeholders to achieve goals.
Contribute to the evolution of the data ecosystem by designing AI ready architectures and scalable solutions.
Collaborate with Agile teams to design, develop, implement, and support technical solutions across the organization.
Work with a team of developers experienced in machine learning, AI, distributed microservices, and full stack systems.
Share expertise by staying current with technology trends, experimenting with new tools, participating in internal and external communities, and mentoring other engineers.
Partner with digital product managers to deliver robust cloud based solutions that enable powerful experiences for millions of Americans seeking financial empowerment.

Requirements

Bachelor’s Degree.
At least 4 years of experience in application development (internship experience does not apply).
At least 2 years of experience with big data technologies.
At least 1 year of cloud computing experience with AWS, Microsoft Azure, or Google Cloud.

Technologies

SQL, Spark, Python, Scala, Java
MapReduce, Hadoop, Hive, EMR
Kafka, Gurobi, MySQL
MongoDB, Cassandra
Redshift, Snowflake
AWS, Microsoft Azure, Google Cloud
UNIX/Linux, shell scripting
Data Lake, Data Warehouse

Benefits

Health benefits
Financial benefits
Performance-based incentives (cash bonuses and/or long-term incentives)

Basic Qualifications

Bachelor’s Degree
At least 4 years of experience in application development (internship experience does not apply)
At least 2 years of experience with big data technologies
At least 1 year of cloud computing experience with AWS, Microsoft Azure, or Google Cloud

Preferred Qualifications

4+ years of experience in Data Architecture / Data Modeling
7+ years of experience in application development including Python, SQL, Scala, or Java
4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)
4+ years of experience with distributed data / computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)
4+ years of experience working on real time data and streaming applications
4+ years of experience with NoSQL implementations (Mongo, Cassandra)
4+ years of data warehousing experience (Redshift or Snowflake)
4+ years of experience with UNIX/Linux including basic commands and shell scripting
2+ years of experience with Agile engineering practices
Experience leveraging interactive AI tooling to accelerate productivity beyond basic code completion

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11d ago

Data Analyst - AI Trainer

DataAnnotation Richmond, VA 🇺🇸 Remote

Richmond, VA

11d ago

$50 - $100/hr Full time Ai Trainer Analyst Analytics

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Job Description

This fully remote Data Analyst - AI Trainer role focuses on designing coding problems to train AI systems, evaluating AI-generated code, and shaping future AI models.

Responsibilities

Create and solve a variety of coding challenges used to train AI systems.
Produce concise, well-documented code samples with thorough explanations.
Assess AI-generated code for accuracy, performance, and clarity.
Offer feedback that informs the next generation of AI models.

Requirements

Fluent in English (native or bilingual level).
Proficiency in at least one of these languages or frameworks: JavaScript, TypeScript, Python, C, C#, C++, React, Go, Java, Kotlin, or Swift.
Excellent writing and grammar skills.
Bachelor’s degree (completed or in progress).

Technologies

JavaScript
TypeScript
Python
C
C#
C++
React
Go
Java
Kotlin
Swift

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: select projects and set your own work timing.
Competitive pay: hourly projects, up to $100+ USD per hour, with opportunities to earn more based on performance.
Impact: contribute to shaping the future of AI technologies.

Compensation

Pay: $50.00 - $100.00 per hour

Location

Remote; based in Richmond, Virginia

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30d ago

Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS)

Capital One Richmond, VA

Richmond, VA

30d ago

$179k - $205k/yr Full time AWS Big Data Cloud

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Job Description

Capital One is seeking a Lead Machine Learning Engineer to scale ML solutions across the organization, focusing on architecture, model development, deployment, and operations within an Agile environment. This role centers on productionizing ML applications and systems, building robust data pipelines, and delivering ML capabilities at scale.

Location

Richmond, VA (onsite)

Compensation

Salary: USD 179,400 - 204,700 per year

Responsibilities

Design, build, and deliver ML models and components that address real-world business problems, partnering with Product and Data Science teams.
Inform ML infrastructure decisions using knowledge of modeling techniques, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Collaborate within a cross-functional Agile team to create and improve software for state-of-the-art big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and code.
Ensure code quality and governance, manage risk for models, and adhere to Responsible and Explainable AI practices.
Use programming languages such as Python, Scala, or Java.

Requirements

Bachelor’s degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems

Technologies

KServe, Kubernetes, PyTorch, TensorFlow
AWS, Python, Scala, Java
scikit-learn, Dask, Spark

Benefits

This role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Incentives can be discretionary or non-discretionary depending on the plan.
Health, financial, and other benefits that support total well-being.

Team Description

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in res

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Data Jobs in Richmond, VA

Lead Data Engineer (Finance Tech)

Data Engineer, Finance Data & BI

Lead Data Engineer - Data Transformation (Modeling and Architecture)

Data Analyst - AI Trainer

Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS)

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