Collaboration

Collaboration Data Jobs

13 jobs found

Today

Data Engineer

Youth Villages Chesterfield, VA

Chesterfield, VA

Today

Full time Analytics Big Data Business Analytics

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Job Description

You’ll help Youth Villages design and modernize cloud-based data foundations that power trusted reporting, analytics, and day-to-day operational decisions. This onsite role in Chesterfield, VA focuses on building scalable ELT/ETL pipelines, developing and optimizing Snowflake data warehouse structures, and strengthening data governance, quality, and modernization of legacy reporting workflows.

What you’ll bring

Bachelor’s degree in Computer Science, Information Systems, Engineering, Business Analytics, or a related field (preferred)
ETL/ELT experience developing and implementing enterprise data solutions (required)
Experience with Snowflake, SQL Server, MySQL, Fivetran, Coalesce, and GitHub (preferred)
SQL strength including query development and query optimization
Agile experience
Data warehousing concepts and data governance best practices
Strong organizational skills, attention to detail, and effective written, verbal, and oral communication
Ability to manage multiple priorities and maintain a flexible schedule
Comfort supporting secure and compliant handling of sensitive PHI data

Key responsibilities

Build scalable cloud data solutions that adapt as business needs and source systems change
Design, develop, and maintain ELT/ETL pipelines using modern cloud technologies and data integration platforms
Develop and optimize data ingestion and transformation processes using Snowflake, SQL Server, MySQL, Fivetran, Coalesce, SQL, and GitHub
Maintain and improve enterprise data warehouse structures, curated datasets, and transformation logic supporting reporting and analytics
Optimize SQL queries and warehouse performance for accuracy, scalability, and efficiency
Collaborate with business and technical teams to translate requirements into technical solutions
Monitor, troubleshoot, and improve data workflows and production data processes
Support data governance with metadata management, lineage tracking, documentation, and data quality validation
Diagram and document data flows, integrations, schemas, and transformation logic
Support Tableau initiatives by delivering validated, high-quality datasets for dashboards and analytics
Participate in Agile activities including sprint planning, estimation, backlog grooming, and release support
Perform other duties as assigned

Growth and benefits

You can expect a benefits package that includes:

Medical, Dental, Prescription Drug Coverage, and Vision
401(k)
Time off: 2 week paid vacation (full-time) / 1 week paid vacation (part-time), plus 12 paid sick days per year and 11 paid holidays
Paid Parental Leave
Mileage & Cell Phone Reimbursement (when applicable)
Tuition reimbursement and licensure supervision
Growth & development through continuous training
Clinical and administrative advancement opportunities
Benefits are excluded for variable status employees.

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1mo ago

Analytics Engineer

General Dynamics Information Technology Remote 🇺🇸 Remote

Remote

1mo ago Closed

$128k - $173k/yr Full time Analytics Apache Airflow Big Data

This position is no longer accepting applications (closed Sep 14, 2026).

Job Description

Make data engineering more reliable, scalable, and usable. As a Senior Analytics Engineer with General Dynamics Information Technology, you will design automated pipelines and analytics-ready datasets, then deliver dashboards and analytical models that help teams make faster, more informed decisions across multiple business and program areas.

This fully remote role supports end-to-end work from data preparation through modeling and reporting, with opportunities to collaborate with data engineers, analysts, software developers, and stakeholders. The likely salary range for this position is $127,500 to $172,500, depending on experience and qualifications.

Responsibilities

Design, build, and maintain automated, scalable ETL/ELT pipelines using Python, SQL, and cloud-based tools to integrate, transform, and validate structured and unstructured data.
Develop and manage analytics-ready data models and workflows (for example in Databricks or similar platforms) to support reporting, self-service analytics, and advanced data science use cases.
Implement CI/CD practices with GitLab to keep analytics and data engineering processes reliable, versioned, and repeatable.
Build interactive dashboards and reports using Tableau, Power BI, or similar tools to deliver complex analysis to business and technical stakeholders.
Perform data mining, cleaning, and manipulation with SQL and Python (including Pandas and NumPy) to support statistical analysis, visualizations, and decision-support tools.
Own end-to-end analytical and modeling activities such as exploratory data analysis, feature preparation, model validation, and documentation, with experience in AI or predictive modeling considered a plus.
Collaborate across teams to translate business requirements into effective data models, pipelines, and visualizations.
Compile and maintain metadata, data dictionaries, and technical documentation, and produce recurring and ad-hoc reports for leadership.
Handle urgent and ad-hoc data requests and support collaborative research and analysis across program areas.
Provide technical guidance and mentorship on analytics best practices, Python scripting, data modeling, and workflow automation.

Requirements

Bachelor’s degree in a quantitative field (data science, Computer Science, Statistics, Mathematics, Engineering, or related) plus 5+ years of experience, or 3+ years with a Master’s degree in analytics engineering, data engineering, or data analysis.
Strong proficiency in Python, SQL, and Git/GitLab, including experience building ETL/ELT pipelines with CI/CD and data engineering best practices.
Experience with relational and non-relational databases (for example Oracle and PostgreSQL) and creating executive-ready dashboards using Tableau or Power BI.
Strong analytical and problem-solving skills with attention to detail, including the ability to work with large, complex datasets and communicate insights to technical and non-technical audiences.
Ability to work independently and collaboratively in fast-paced, agile environments, with excellent written and verbal communication skills.
Fully remote role with a Public Trust (or ability to obtain it); US citizenship required.

Technologies

Python, SQL, GitLab, Git, Tableau, Power BI, Databricks, Pandas, NumPy, Airflow, MLflow, Oracle, PostgreSQL, AWS, CI/CD, ETL, ELT

Work Requirements

Travel Required: None
Citizenship: U.S. Citizenship Required
Years of Experience: 5+ years of related experience (may vary based on technical training, certification(s), or degree)

Identity Verification Process

Identity verification process leveraging advanced biometrics and artificial intelligence
Expected to be on camera during virtual interviews
May be required to be on camera and authorize collection, processing, and use of biometric data for identity verification and security purposes

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1mo ago

Data and Analytics Engineer

Virginia Tech Blacksburg, VA

Blacksburg, VA

1mo ago Closed

$95k - $103k/yr Full time Analytics Apache Airflow Artificial Intelligence

This position is no longer accepting applications (closed Sep 14, 2026).

Job Description

Virginia Tech is hiring a Data and Analytics Engineer to help design, develop, and support enterprise data products, cloud data pipelines, and analytics solutions that power institutional reporting, decision support, advanced analytics, and AI initiatives. This hybrid role in Blacksburg, VA supports modern, secure, cloud-based data capabilities while partnering with stakeholders to deliver trusted, governed, reusable data assets.

In this position, you will contribute to Virginia Tech’s enterprise data and analytics strategy by building scalable data solutions and enabling self-service analytics that support research, operational excellence, and strategic decision-making.

Responsibilities

Design, develop, and support enterprise data products, cloud data pipelines, and analytics solutions across Virginia Tech to support institutional reporting, decision support, advanced analytics, and AI initiatives.
Develop scalable and secure data solutions using Snowflake, AWS, Power BI, and related technologies.
Partner with business stakeholders, data stewards, and technical teams to transform institutional data into trusted, governed, reusable data assets for self-service analytics, operational excellence, research, and strategic decision-making.
Support the enterprise data and analytics strategy through the development and ongoing support of modern cloud-based data solutions.

Requirements

Master’s degree, or an equivalent combination of education, training, and progressive experience.
Experience designing, developing, supporting, and optimizing enterprise data, reporting, and analytics solutions.
Significant experience with programming, scripting, or automation for data engineering and analytics, such as Python, SQL, or similar tools.
Significant experience with relational databases such as Oracle, Postgres, or Snowflake, plus advanced SQL.
Experience with SQL development, data transformation, query optimization, and working with enterprise-scale relational and analytical data platforms.
Experience translating business requirements into scalable technical solutions for data management, reporting, analytics, and decision-making.
Experience developing and supporting data transformation, data pipelines, and/or enterprise data platforms.
Experience with cloud-based data, analytics, or enterprise application platforms.
Experience with data modeling, data quality management, metadata management, data governance, and enterprise data security principles.
Strong analytical, troubleshooting, and problem-solving skills.
Ability to communicate effectively with technical and non-technical audiences and collaborate across cross-functional teams.
Ability to manage multiple priorities and deliver high-quality solutions in a dynamic environment.

Technologies

Snowflake, AWS, Power BI, Python, SQL, Oracle, Postgres, Snowpark, Dynamic Tables, Streams and Tasks, Data Sharing, Horizon Catalog and Governance, Cortex AI services, dbt, Apache Airflow, Terraform, Git

Preferred Qualifications

Experience designing, implementing, and supporting Snowflake-based data platforms in production.
Experience using Snowflake platform capabilities including Snowpark, Dynamic Tables, Streams and Tasks, Data Sharing, Horizon Catalog and Governance, and Cortex AI services.
Experience with analytics engineering and modern data stack technologies such as dbt or similar transformation frameworks.
Experience supporting DataOps practices, including automated testing, deployment pipelines, monitoring, observability, and operational automation.
Experience with workflow orchestration tools such as Apache Airflow or comparable technology.
Experience with infrastructure-as-code using Terraform.
Experience supporting machine learning, predictive analytics, artificial intelligence, or generative AI initiatives.
Experience developing enterprise data products, semantic models, or reusable analytics assets for self-service analytics and institutional decision-making.
Experience integrating enterprise applications, SaaS platforms, and APIs with modern cloud data platforms.
Experience with higher education data domains (student, finance, human resources, advancement, research, or academic operations).
Experience building dashboards, reports, semantic models, or self-service analytics solutions using enterprise BI platforms such as Power BI, Tableau, MicroStrategy, or comparable tools.
Experience using source control and collaborative development practices with Git or comparable platforms.
Experience supporting software development lifecycles including solution design, development, testing, deployment, documentation, and operational support.
Experience developing and supporting cloud-based data platforms, data integration processes, and data pipelines using AWS or comparable cloud technologies.
Experience developing, maintaining, and supporting data pipelines, ETL/ELT processes, and related data engineering solutions enabling reporting, analytics, and business operations.

Role Details

Location: Blacksburg, VA (hybrid)
Appointment type: Regular
Salary: $95,000 - $102,750 per year
Hours: 40 hours per week
Overtime status: Exempt (not eligible for overtime)
Review date: 8/18/26

Additional information: A criminal conviction check is required. Sponsorship is not available for this position.

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1mo ago

Vice President, Data Products & Analytics Engineer

MUFG Jersey City, NJ

Jersey City, NJ

1mo ago Closed

$153k - $237k/yr Full time Analytics Atlassian Business Analytics

This position is no longer accepting applications (closed Aug 30, 2026).

Job Description

MUFG seeks a senior individual contributor to lead data product strategy and execution within Data Management Engineering. This role shapes roadmaps for data products and enables analytics, reporting, and AI enabled data consumption across the enterprise. Based in Jersey City, NJ with a hybrid work arrangement, the position carries a salary range of USD 153,000 to 237,000 per year and requires a bachelor’s degree with at least seven years of relevant experience.

Responsibilities

Develop and sustain trust-based relationships with key stakeholders to comprehend business challenges and identify data solutions that advance objectives.
Empower business and corporate functions with robust data capabilities, ensuring clear lineage to products, services, and processes, delivering contextually valuable insights, and enabling seamless data access.
Optimize the data product lifecycle to modernize assets and maximize value, identifying process improvements to advance governance, management, and utilization.
Engage data users proactively to improve data maturity, adoption, and self-service while fostering a culture of continuous improvement and systems thinking.
Collaborate with senior business stakeholders to align data products with strategic objectives and address analytics, reporting, and consumption challenges.
Contribute to the technical and product direction for a portfolio of enterprise data products, translating complex processes into curated, reusable, and governed data assets.
Provide expertise on end-to-end data product lifecycle, including sourcing, design, engineering, quality, certification, and consumption readiness.
Translate business and analytics requirements into clear data engineering specifications and implementation plans, applying modern data architecture patterns for scalable consumption.
Collaborate across engineering and analytics teams to promote common standards, tooling, and delivery practices within a matrixed environment.
Enable advanced data consumption capabilities, including BI, self-service analytics, and AI assisted querying under governed access controls.
Support data literacy and adoption through documentation, data catalogs, and enabling business data users.

Requirements

10+ years of data experience in Banking and Financial Services from technology, data, or business operations perspectives.
10+ years of experience in data management and/or data product development.
7+ years of experience in business, systems, and data architecture and analysis.
Proven experience as a Data Engineer and/or Business Data Architect or similar role, with a focus on business value creation and enablement.
Bachelor’s degree in science, business, management, or finance-related fields.
Advanced degree is a plus.

Technologies

Snowflake
AWS based data services
Collibra
Starburst
Informatica
Tableau
PowerBI
Alteryx
Relational databases and enterprise data warehouse technologies
Jira
Confluence

Benefits

Comprehensive health and wellness benefits
Retirement plans
Educational assistance and training programs
Income replacement for qualified employees with disabilities
Paid maternity and parental bonding leave
Paid vacation, sick days, and holidays

Data Products & Engineering Expertise

Proven success modernizing data ecosystems through cloud platforms, automation, and integrated data solutions that enhance data quality, accessibility, governance, and enable advanced analytics and AI enabled data consumption.
Experience designing, scaling, and operating modern data architectures, including data marts, validation, and reconciliation frameworks for end-to-end analytics and regulatory use cases.
Hands-on proficiency with cloud-based data platforms and contemporary data architectures.
Advanced SQL skills and strong experience with data transformation, profiling, validation, and reconciliation frameworks.
Practical understanding of AI enabled data access patterns (semantic layers, natural language querying, curated retrieval) in regulated environments.
Solid grounding in metadata management, lineage, data quality controls, and certification workflows.
Experience across business, data, and application architecture and process re-engineering.

Leadership, Influence & Business Acumen

Expertise in business requirements analysis, design, and functional/detail design within Banking and Financial Services.
Ability to operate with senior-level autonomy and influence across business, technology, and risk functions.
Strong executive communication skills, capable of translating technical concepts into clear business terms; detail-oriented while maintaining strategic focus.
Effectiveness in building alignment, driving adoption, and managing competing priorities within a matrixed organization.
Product-oriented mindset with balanced emphasis on near-term delivery, risk management, and long-term platform sustainability.
Proven ability to build consensus across business areas to support new capability models.
Adaptable to rapidly shifting priorities and evolving business needs.

Technology & Tooling

Expert knowledge of cloud platforms, programming languages, and modern software engineering practices.
Cloud data platforms such as Snowflake and AWS based data services
Enterprise data governance and metadata platforms such as Collibra
Data virtualization platforms such as Starburst
ETL tools such as Informatica
BI and analytics tools such as Tableau, PowerBI, Alteryx or equivalent
Relational databases and enterprise data warehouse technologies
Agile delivery and collaboration tools including Jira and Confluence

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1mo ago

Data Scientist

LinQ Global Group Glendale, CA

Glendale, CA

1mo ago Closed

Full time Python A/B Testing Big Data

This position is no longer accepting applications (closed Aug 29, 2026).

Job Description

LinQ Global Group seeks a Data Scientist to design and analyze A/B tests and causal inference studies, partnering with cross-functional teams to generate insights and build scalable experimentation solutions using advanced statistical methods.

Responsibilities

Design and run A/B tests and geo-based experiments to validate ideas and measure impact.
Analyze data with statistical and causal-inference techniques to uncover actionable insights.
Create scalable analytics and experimentation platforms to support ongoing measurement.
Develop statistical models and machine learning solutions to inform business decisions.
Perform sample size planning, power analysis, and post-experiment evaluation to ensure reliable results.
Present findings and recommendations to business stakeholders and leadership.
Collaborate with cross-functional teams to address business problems through data-driven approaches.
Mentor team members and promote best practices in experimentation and data science.

Requirements

Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field.
7+ years of experience in experimentation, causal inference, or data science.
Strong knowledge of A/B testing, experimental design, and statistical modeling.
Experience with causal inference methods such as Difference-in-Differences, Propensity Score Matching, and Instrumental Variables.
Proficiency in Python and/or R.
Experience with machine learning libraries such as scikit-learn or LightGBM.
Strong analytical, problem-solving, and communication skills.

Technologies

Python
R
scikit-learn
LightGBM
Databricks
Snowflake
Jupyter
GitHub

Location

Glendale, CA 91201

Job Type

Full-Time

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1mo ago

Lead Data Engineer

American Red Cross Charlotte, NC 🇺🇸 Remote

Charlotte, NC

1mo ago Closed

$140k - $155k/yr Full time Senior Analytics AWS

This position is no longer accepting applications (closed Aug 29, 2026).

Job Description

The Lead Data Engineer will guide the Enterprise Data & Analytics Team at the American Red Cross in North Carolina, working remotely with in-person meetings as needed and periodic weekend rotations. The role focuses on modernizing data architecture, building and operating an enterprise data warehouse, ensuring data quality, and mentoring team members.

Responsibilities

Collaborate with analytics and business stakeholders to refine data models that feed business intelligence tools, broadening data accessibility and enabling data-driven decision making across the organization.
Design and implement scalable solutions that align with data governance standards and the architectural roadmap for data integrations, storage, reporting, and analytics.
Architect, develop, and validate data integration solutions; automate and document unit, integration, and functional tests.
Oversee automated deployments via Git pipelines to ensure code changes are version-controlled and deployed efficiently.
Coordinate with multiple teams to streamline deployment workflows and monitor pipelines for reliability and performance.
Analyze data to troubleshoot issues by establishing a data quality framework and supporting issue resolution.
Serve as technical lead by mentoring junior engineers through code reviews, pair programming, and other hands-on activities.

Requirements

A 4-year college degree in Computer Science, Engineering, Mathematics, or a related technical field, or an equivalent combination of education and experience.
10 years of relevant experience in data engineering, business intelligence, or a related field.
Authorized to work in the United States; the organization does not sponsor employment visas.
Experience with a variety of database technologies and data warehouse schema design patterns.
Cloud-based databases with a focus on AWS technologies.
Advanced SQL skills, including writing and optimizing queries for large-scale, complex datasets.
Proficiency in Python programming.
Experience using AI-assisted development tools such as GitHub Copilot and Duo across the software development lifecycle.
Experience creating ETL and/or ELT jobs.
Familiarity with DevOps practices and tools, including Git and Artifactory.
Knowledge of Agile software development methodologies.
Proven ability to lead data engineering teams in an onshore/offshore model, mentoring junior engineers and establishing best practices.
Strong problem-solving and troubleshooting capabilities.
Process-oriented mindset with strong documentation skills.
Commitment to the humanitarian mission of the Red Cross.

Technologies

AWS technologies
SQL
Python
Git
GitHub Copilot
Duo
ETL/ELT
Artifactory
DBT
Reltio
Profisee
Redshift
Snowflake
Star

Benefits

Medical, Dental, & Vision Plans
Health Spending Accounts & Flexible Spending Accounts
PTO and Holidays
401K with up to 6% Match
Paid Family Leave
Employee Assistance Programs
Disability and Insurance: Short and Long Term
Service Awards and Recognition

Pay Information

Annual salary range: $140,000 - $155,000
No annual bonus is offered for this role
Salaries are aligned to the geographic location where the work is primarily performed
Other factors influencing salary may include specific skills, years of experience, and comparison to others in similar roles
Salary details will be reviewed at the time of phone screening based on location and experience
The job posting remains active for a minimum of five business days and may be extended if the applicant pool requires expansion

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1mo ago

Data Scientist

Leidos Maryland 🇺🇸 Remote

Maryland

1mo ago Closed

$70k - $126k/yr Full time Python Analytics Artificial Intelligence

This position is no longer accepting applications (closed Aug 23, 2026).

Job Description

Data Scientist at Leidos focused on mission-focused big data and predictive analytics for national security, with research-level analytics and cross-functional collaboration, and flexible on-site/remote work based on client requirements.

Responsibilities

Collaborate with a cross-disciplinary team of data scientists, software engineers, network specialists, senior investigators, program managers, researchers, and data analysts to design, build, and refine a Search and Discovery platform that locates, organizes results, disseminates findings via reports, and supports publications and presentations.
Pursue research tasks to identify optimal indexing and data organization strategies to enhance discovery.
Develop agents and tools as reusable elements within a broader agent-based solution space.
Manage multiple concurrent projects, use open-ended guidance, and independently or with teammates uncover mission-relevant insights, then package and present findings to non-technical audiences.
Apply curiosity, quantitative acumen, and customer focus to identify novel data sources across fields, improve predictive algorithm performance, and promote adoption of advanced data analytics platforms with a skilled, motivated team.
Utilize expertise in research design, exploratory analysis, quantitative methods, UI application design, and customer outreach and engagement.

Requirements

Bachelor's degree in a quantitative or analytical field (examples include Computer Science, Mathematics, Economics, Statistics, Engineering, Physics, or Computational Social Science) or Master's degree or equivalent graduate degree with certificate-based advanced training.
4+ years of experience in data science, analytics, or quantitative intelligence analysis, demonstrating progressive technical development; with a Master's degree, 2+ years of experience is required.
Active TS/SCI clearance required; able to obtain and maintain a polygraph.
Proficient in Python.
Experience deploying data science applications (for example Streamlit) using Docker, Kubernetes, and/or OpenShift.
Experience with information retrieval and search technologies, such as Elastic Stack (Elasticsearch, Kibana) and SQL.
Familiar with Git and cooperative software development practices.
Experience working with a hybrid team of analysts, engineers, and developers to research, build, and deploy complex yet user-friendly algorithms and analytics platforms.
Demonstrated active learning and creative problem solving.
Experience in co-development and cooperative research to maximize reuse of team products.