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4d ago

Senior Data Analyst - Global Payment Network

Capital One Riverwoods, IL

Riverwoods, IL

4d ago

$101k - $115k/yr Full time Senior Analyst Analytics

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Job Description

Join Capital One's Global Payment Network analytics team in Riverwoods, IL, on a hybrid schedule, and tap into a benefits-forward environment that values innovation, business intelligence, and data governance. This role centers on building data solutions, dashboards, and governance workflows in AWS, with a culture that emphasizes collaboration, self-service analytics, and data quality. You will benefit from health and financial benefits, plus performance-based incentives that recognize contributions to business outcomes.

Responsibilities

Leverage open source and digital technologies to mine complex, large-scale data from diverse sources and platforms
Design and deliver well-managed data solutions, tools, and capabilities that enable self-service analytics for data consumers
Rapidly explore and adopt new technologies to drive multiple initiatives forward
Partner with the business to translate needs into tools, techniques, metrics, and dashboards for insights and visualization
Lead analyses that inform and shape business strategies
Promote and ensure adherence to data quality management principles, including metadata, lineage, and business definitions
Collaborate with technology teams to manage security mechanisms and data access governance
Develop and deploy tools to monitor and report on data quality

Requirements

Currently pursuing or possessing a Bachelor’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or related) with at least 2 years of data analytics experience; or pursuing a Master’s degree with expected completion by the start date
At least 1 year of experience working with at least one scripting language
At least 1 year of experience using a business intelligence visualization tool
At least 1 year of experience querying, analyzing, and working with data languages and platforms

Technologies

Python
R
Spark
SQL
AWS
Informatica DQ

Benefits

Health benefits
Financial benefits
Incentives (performance-based incentive compensation, including cash bonuses and/or long term incentives)

Our ideal candidate will have

A degree in a Science, Technology, Engineering, or Mathematics discipline
Scripting experience in Python, R, Spark, and SQL
A strong interest in data in diverse forms, including data warehouses/SQL and unstructured data
Experience using and building within AWS services

Basic qualifications

Currently pursuing or possessing a Bachelor’s degree in a quantitative field with at least 2 years of data analytics experience; or pursuing a Master’s degree with anticipated completion by the start date
At least 1 year of experience with at least one scripting language
At least 1 year of experience using a BI visualization tool
At least 1 year of experience querying, analyzing, and working with data languages and platforms

Preferred qualifications

Master’s degree in a STEM discipline
At least 2 years of experience coding in Python, R, Spark, or SQL
At least 2 years of experience with process management and improvement methodologies such as Agile, Lean, or Six Sigma
At least 1 year of experience using AWS services
At least 1 year of experience with data governance and data quality concepts and tools (for example Informatica DQ)

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4d ago

Senior Data Analyst

UnitedHealth Group Draper, UT 🇺🇸 Remote

Draper, UT

4d ago

$92k - $164k/yr Full time Senior Analyst Analytics

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Job Description

UnitedHealth Group, Optum, is seeking a Senior Data Analyst in Draper, UT with remote options. The role centers on credit analytics, building data pipelines, dashboards, and reports to inform credit risk, underwriting, and portfolio decisions. This position offers a comprehensive benefits package, incentive and recognition programs, equity stock purchase, and a 401k contribution.

Benefits

Comprehensive benefits package
Incentive and recognition programs
Equity stock purchase
401k contribution

Responsibilities

Act as a senior analytics partner to the Credit team, delivering data-driven insights across credit risk, portfolio performance, underwriting, and loss mitigation
Design, optimize, and maintain complex SQL queries to extract, transform, and analyze large volumes of financial and credit data from enterprise data warehouses
Use Python with libraries such as pandas and NumPy to perform advanced data analysis, automate workflows, validate results, and engineer features, complementing SQL-based workflows and boosting analytical efficiency
Create and maintain interactive Power BI dashboards and reports to deliver clear, actionable insights to Credit leadership and stakeholders
Develop and sustain SSRS reports to support operational, regulatory, and management reporting needs, ensuring accuracy, consistency, and timeliness
Conduct advanced Excel analysis with pivot tables, Power Query, Power Pivot, and complex formulas to support ad hoc requests and deep-dive investigations
Analyze credit metrics including delinquency, roll rates, charge-offs, recoveries, exposure, and vintage performance to identify trends, risks, and opportunities
Collaborate with Credit Risk, Underwriting, Finance, and Compliance to ensure reporting aligns with business rules, policies, and regulatory expectations
Validate data integrity and reconcile results across multiple systems to ensure reporting accuracy and reliability
Translate complex analytical findings into clear, concise insights and recommendations tailored to technical and non-technical audiences
Support automation and process improvements to increase efficiency, scalability, and self-service analytics within the Credit organization
Mentor junior analysts and contribute to the development of best practices for SQL, reporting standards, and analytical methodologies
Ensure adherence to data governance, security, and regulatory requirements specific to banking and credit data

Requirements

Bachelor's degree in Data Analytics, Finance, Economics, Statistics, Information Systems, or related field, or equivalent practical experience
5+ years of experience in data analytics, with direct experience supporting Credit, Credit Risk, or Lending teams within a bank or financial services organization
Advanced Power BI skills, including data modeling, DAX, custom measures, and executive-ready dashboards
Hands-on SSRS report development, maintenance, and support in a production environment
Solid working knowledge of credit concepts such as delinquency, charge-offs, recoveries, exposure, vintages, utilization, and portfolio performance
Advanced Python proficiency, including pandas, NumPy, and related analytical packages for data manipulation, validation, automation, and large-scale analysis; experience building reusable scripts or pipelines is highly valued
Expert SQL proficiency, including complex joins, CTEs, subqueries, window functions, and performance-optimized queries on large datasets
Advanced Excel skills, including pivot tables, Power Query, Power Pivot, complex formulas, and statistical or financial analysis
Ability to validate data, reconcile across multiple source systems, and ensure high data quality and reporting accuracy
Strong analytical and problem-solving skills with the capacity to independently investigate issues and deliver insights
Excellent communication skills for explaining complex data findings to technical and non-technical stakeholders

Technologies

Technologies: Python, pandas, NumPy, SQL, Power BI, SSRS, Excel, Power Query, Power Pivot, DAX

Preferred Qualifications

Experience with consumer or commercial lending products such as credit cards, auto loans, personal loans, mortgages, or commercial loans
Experience with large enterprise data warehouses and financial systems
Experience building automated or self-service reporting solutions for business users
Experience using Python for automation, process optimization, or advanced analytics (trend analysis, scenario analysis, or custom performance monitoring)
Experience developing, validating, or deploying analytical models using Python, including feature engineering, model evaluation, and performance monitoring in a financial or risk analytics context
Experience supporting senior leadership with executive-level reporting and insights
Familiarity with banking regulatory and risk frameworks (CECL, stress testing, portfolio monitoring, audit support)
Demonstrated ability to mentor junior analysts and establish analytics best practices

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4d ago

Social Media and Marketing Coordinator and Google Analytics

JW Truck Sales, Inc Flowery Branch, GA

Flowery Branch, GA

4d ago

$18 - $24/hr Full time Marketing Analytics Brand Management

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Job Description

JW Truck Sales, Inc is seeking a dynamic Social Media and Marketing Coordinator with Google Analytics expertise to craft digital narratives, manage social media campaigns, analyze performance, and optimize marketing strategies.

Responsibilities

Plan and execute engaging social media campaigns across Facebook, Instagram, Twitter, LinkedIn, and other networks to elevate brand visibility and audience engagement.
Coordinate daily publishing calendars with tools such as Hootsuite or Buffer to maintain consistent messaging aligned with the brand voice.
Produce compelling visuals and copy, including graphics, videos, photography, and written posts, using Adobe Photoshop, Illustrator, and Creative Suite.
Perform social listening to track brand mentions, industry trends, and competitor activity to guide content planning and reputation management.
Run targeted Facebook ad campaigns aimed at defined audiences to drive traffic and conversions.
Analyze site traffic and campaign performance with Google Analytics and other analytics tools; deliver reports highlighting insights and recommended actions.
Work with the PR team to develop press materials, manage media relationships, and support brand initiatives.
Support ecommerce by aligning social campaigns with online sales channels and measuring ROI.
Proofread content for accuracy, clarity, and brand consistency prior to publication to maintain high-quality standards.

Requirements

Proven track record in social media management, digital marketing, and content creation with solid understanding of platform algorithms.
Knowledge of SEO techniques to boost online visibility through keyword research and optimized content strategies.
Proficient in graphic design with Photoshop, Illustrator, and Creative Suite; basic video editing is a plus.
Experience with social listening tools like Hootsuite or Buffer to monitor brand reputation and industry trends.
Experience with Facebook Advertising to create targeted campaigns that maximize engagement.
Strong analytical abilities with Google Analytics experience to interpret data trends and assess campaign performance.
Excellent proofreading to ensure polished, accurate content aligned with brand standards.
Ability to manage multiple projects concurrently with attention to detail in a fast-paced setting.
Strong relationship management skills for cross-functional collaboration with PR, sales, and creative teams.

Technologies

Facebook
Instagram
Twitter
LinkedIn
Hootsuite
Buffer
Google Analytics
Adobe Photoshop
Adobe Illustrator
Adobe Creative Suite
Facebook Advertising Platform

Benefits

Health insurance
Paid time off

Pay

$18.00 - $24.00 per hour

Expected Hours

40 hours per week

Work Location

In person — Flowery Branch, GA (onsite)

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4d ago

Senior Analytics Engineer

Orchard New York, NY

New York, NY

4d ago

$135k - $180k/yr Full time Senior Analytics Business Intelligence

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Job Description

Orchard seeks a Senior Analytics Engineer in New York, NY (hybrid) to rebuild how the business derives answers from data and to own the analytics platform roadmap end to end.

Responsibilities

Own the major analytics platform initiatives from scoping to delivery, collaborating with the Director to shape future roadmap directions.
Ingest new data sources and deliver production gold-tier dbt models that the company can rely on, balancing speed and quality.
Author and maintain the prose semantic layer with markdown documentation describing model meanings, metric definitions, historical decisions, and known landmines.
Develop and tune the LLM-powered query layer, including prompt design, retrieval workflows, evaluation, and the feedback loop when results are incorrect.
Deploy and calibrate agents that monitor certified dashboards for anomalies and trend shifts, refining them until executives trust the alerts and act upon them.

Requirements

4+ years in analytics engineering, data engineering, or a hybrid data role, including ownership of a significant data platform or end-to-end migration.
Deep dbt and SQL fluency with strong opinions about data grain, testing, documentation, and the limits of each approach.
Experience working in Redshift or a comparable data warehouse at scale.
Built something useful with LLMs against your own data and have opinions about what works; hands-on experience with retrieval or evaluations is a plus.
Clear technical writing ability; able to explain a metric in a paragraph that an executive can read.
Proven track record of owning technical decisions and bringing stakeholders along across the organization; able to push back when data does not support requests while maintaining collaboration.

Technologies

Looker
dbt
SQL
Redshift
LLM

Compensation

Salary: USD 135,000 - 180,000 per year

Benefits

Stock options
Incentive pay
Medical benefits
Financial benefits
Other benefits

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4d ago

Associate Data Engineer

Baker Tilly Advisory Group, LP Milwaukee, WI

Milwaukee, WI

4d ago

$86k - $163k/yr Full time Analytics Automation Azure Data Factory

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Job Description

The Associate Data Engineer collaborates with cross-functional teams to design, build, and optimize data platforms for mid-market and enterprise clients. Focusing on the Microsoft stack, the role leverages Azure, Synapse, and Microsoft Fabric to convert raw data into analytics-ready assets for dashboards, advanced analytics, and AI use cases.

Location

Milwaukee, WI (onsite)

Compensation

USD 85,910 - 162,890 per year

Responsibilities

Data engineering: Build scalable ETL/ELT pipelines using T-SQL, Python, Azure Data Factory or Fabric Data Pipelines, and Databricks; apply best practice patterns for performance, security, and cost control.
Modeling and storage: Design relational and lakehouse models; implement Fabric OneLake shortcuts, medallion-style layers, and dimensional/semantic models for Power BI.
Quality and governance: Create automated data quality checks, lineage, and observability metrics; contribute to CI/CD workflows in Azure DevOps or GitHub.
Client delivery: Gather requirements, demonstrate iterative deliverables, document technical designs, and translate complex concepts for non-technical audiences.
Continuous improvement: Explore new capabilities, share findings in internal communities of practice, and contribute to reusable accelerators. Collaborate with clients and internal stakeholders to design scalable data engineering solutions.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field, or equivalent experience.
2–3 years delivering production data solutions, preferably in a consulting or client-facing role.
Strong T-SQL for data transformation and performance tuning.
Python for data wrangling, orchestration, or notebook-based development.
Hands-on ETL/ELT with at least one Microsoft service (Azure Data Factory, Synapse Pipelines, or Fabric Data Pipelines).
Project experience with Microsoft Fabric (OneLake, Lakehouses, Data Pipelines, Notebooks, Warehouse, Power BI DirectLake) preferred.
Familiarity with Databricks, Delta Lake, or comparable lakehouse technologies preferred.
Exposure to DevOps (YAML pipelines, Terraform/Bicep) and test automation frameworks preferred.
Experience integrating SaaS/ERP sources (e.g., Dynamics 365, Workday, Costpoint) preferred.

Technologies

T-SQL
Python
Azure Data Factory
Fabric Data Pipelines
Databricks
Fabric OneLake
Power BI
Azure DevOps
GitHub
Microsoft Fabric
Azure Synapse
Azure
Notebooks
Delta Lake
Dynamics 365
Workday
Costpoint
Terraform
Bicep
YAML pipelines
Power BI DirectLake

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4d ago

Data Engineer II, AAE

Amazon Development Center U.S., Inc. Bellevue, WA

Bellevue, WA

4d ago

$132k - $179k/yr Full time Analytics Apache Airflow Artificial Intelligence

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Job Description

Based in Bellevue, WA onsite, this Data Engineer II role focuses on building end-to-end data platforms for AWS AI services and delivering executive insights through automated analytics and revenue reporting.

Responsibilities

Architect and implement complete data platforms for new AWS AI services, establishing schemas, data models, ETL/ELT pipelines, and analytics infrastructure where none exists today
Develop and maintain production ETL/ELT pipelines with AWS Glue, Airflow, Spark, and Python to ingest data from operational, commercial, and telemetry sources into unified data models
Create agentic data workflows featuring automated reporting pipelines that leverage AI/ML to generate business insights, weekly business review summaries, and anomaly detection with minimal manual intervention
Build event-driven data architectures using CDK, Lambda, SNS/SQS, and S3 event notifications to support real-time data ingestion and processing
Develop executive dashboards and self-serve analytics using QuickSight for VP/GM-level leadership across multiple service lines
Ensure revenue data accuracy by implementing and validating revenue attribution models, discount calculations, and financial data pipelines that feed CFO-mandated reporting
Design data models that support both operational analytics (feature adoption, customer health, churn signals) and financial reporting (revenue, billing, forecasting)
Collaborate with Product Management, Finance, Service Engineering, GTM, and Data Science teams to translate business questions into scalable data solutions
Optimize pipeline performance by reducing runtimes, eliminating redundant processing, and improving SLA compliance across production workloads
Mentor engineers, contribute to team standards, and foster a culture of automation, code quality, and operational excellence

Requirements

5+ years of data engineering experience
3+ years of developing and operating large-scale BI data structures for analytics using ETL/ELT processes
3+ years of developing and operating large-scale BI data structures for analytics using data modeling
Experience with data modeling, data warehousing, and building ETL pipelines

Technologies

AWS Glue
Redshift
Athena
QuickSight
Bedrock
SageMaker
CDK
Lambda
SNS
SQS
S3
Airflow
Spark
Python
Kendra
Kiro

Benefits

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)

A day in the life

Design data models for newly launched AWS AI services and deploy ETL pipelines to onboard telemetry and revenue data
Validate data accuracy across financial reporting systems
Architect CDK-based event-driven pipelines and collaborate with Product Managers to define launch metrics
Resolve data discrepancies surfaced by Finance and optimize production queries feeding VP-level weekly business reviews

About the team

The AI Services Data Engineering team builds the data infrastructure behind AWS Armored AI products including Bedrock, AgentCore, QuickSight, Q Business, Kendra, Kiro, and Transform. Our data powers metrics and reporting that inform executive visibility into Agentic AI revenue, adoption, and growth, including automated weekly business reviews with agent-generated summaries and revenue attribution models for multi-billion dollar pricing programs and launch telemetry.

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4d ago

Data Engineer, WW Pricing - Data & Analytics

Amazon.com Services LLC Seattle, WA

Seattle, WA

4d ago

$132k - $179k/yr Full time Amazon S3 Analytics AWS

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Job Description

The Data Engineer role within WW Pricing Data & Analytics at Amazon focuses on building data pipelines and ML data infrastructure to support pricing algorithms and reporting, collaborating with data scientists and business analysts across pricing initiatives.

Location

Seattle, WA (onsite)

Compensation

USD 132,100 - 178,800 per year

Responsibilities

Design and implement next generation data pipelines and business intelligence solutions
Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, and Lambda
Deliver robust data architecture and pipelines to support business analysts, data scientists, and customer reporting needs
Collaborate with other technology teams to extract, transform, and load data from diverse data sources
Improve ongoing reporting and analytics processes, automating self-service capabilities for users

Requirements

Minimum 3 years of data engineering experience
At least 1 year of developing and operating large-scale BI data structures using ETL/ELT processes
At least 1 year of deploying BI data structures with OLAP technologies
At least 1 year of experience in data modeling for large-scale BI data structures
At least 1 year of SQL development and operation in BI contexts
At least 1 year of Oracle experience in BI environments
Experience with data modeling, data warehousing, and building ETL pipelines