Snowflake

Snowflake Data Jobs

100 jobs found

Today

Staff Data Engineer

Okta Chicago, IL

Chicago, IL

Today

$174k - $239k/yr Full time Senior Apache Airflow Cloud

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Job Description

Okta is seeking a Staff Data Engineer to join the Auth0 Data Engineering Team in Chicago, IL on a hybrid schedule. This role leads the architectural evolution of the core data platform, starting with FEDRamp compliance, and drives scalable, secure designs across multiple teams. The position offers a salary range of USD 174,000 to 238,700 per year, with benefits that emphasize well-being, social impact, and talent development within a collaborative culture.

Benefits

Supporting Your Well-Being
Driving Social Impact
Developing Talent and Fostering Connection + Community

The Auth0 Data Engineering Team

Pipeline team — sits near the Platform team and data producers, responsible for efficient data ingestion and rapid access to unmodeled data
Warehouse team — aligns with business teams and data consumers, modeling data in the data warehouse to abstract complexity and simplify analysis, reporting, and decision-making
Interface team — builds and manages connections between the data platform and external systems to ensure consistent and reliable data access

Responsibilities

Spearhead the evolution of the core data platform, shaping the long-term architectural roadmap
Set the technical direction for large-scale platform improvements, balancing visionary goals with incremental delivery
Collaborate with engineers and leaders across data, platform, and security to deliver a cohesive and secure architecture
Create architectural artifacts such as design documents, threat models, and technical specifications to drive clarity and alignment on complex initiatives
Serve as a technical mentor and multiplier for the Data Engineering team, elevating performance through guidance, code reviews, and sharing best practices
Build foundational components of the new architecture, validating designs with hands-on coding and serving as a model for other engineers

Requirements

A passion for building secure, reliable, and scalable data systems
8+ years of software development experience, with at least 5+ years in a data engineering or data platform role
Proven experience designing and delivering large-scale, cross-functional technical projects
Extensive experience architecting and deploying data infrastructure in a cloud environment, with AWS strongly preferred
Deep architectural knowledge of the modern data stack, including data warehouses (Snowflake), transformation tools (dbt), and orchestrators (Airflow)
Strong proficiency in Python and SQL, with a high bar for code quality and system design
Excellent communication skills, with the ability to create clarity and drive decisions on complex technical topics
Ability to deal with ambiguity, define a path forward, and lead others to successful outcomes

Technologies

Technologies: Snowflake, dbt, Airflow, Python, SQL, AWS, Terraform, Kubernetes

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1d ago

Senior Data Engineer

Stellantis Auburn Hills, MI

Auburn Hills, MI

1d ago

Full time Senior Big Data Bigdata

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Job Description

Senior Data Engineer at Stellantis, onsite in Auburn Hills, MI, focused on building reliable data foundations, pipelines and governance to scale AI delivery and industrialize data engineering practices within the Supply Chain AI Hub.

Responsibilities

Design, enhance or govern data models, transformation logic, and pipeline components that enable AI and analytics use cases
Foster maintainable architectures, reusable components, and clear lineage across transformations where applicable
Guide delivery teams with practical data engineering discipline rather than ad hoc builds
Clarify source to platform pathways, integration dependencies, and constraints impacting delivery
Improve visibility of traceability, handoffs, and access controls across the Supply Chain
Collaborate with ICT and engineering stakeholders to keep the build path practical and scalable
Contribute to quality checks, certification routines, governance expectations, or compliance-related traceability as scoped
Surface data structure issues, documentation gaps, or control weaknesses that affect deployment readiness
Support a trusted delivery environment by making data assets more visible, understandable, and maintainable

Requirements

Bachelor's or Master’s degree in Computer Science, Data Engineering, Information Systems, Engineering, Mathematics, or related field
Eight years of experience in data engineering or data platforms
Prior experience in Supply Chain
Hands-on experience with modern data platforms such as Databricks, Spark, Snowflake, or equivalent
Experience with data pipelines, integration, semantics, lineage, architecture and platform environments
Enterprise-scale data transformation and delivery experience
Ability to collaborate effectively with analytics, AI, and software engineering teams

Technologies

Databricks
Spark
Snowflake
SQL

YOUR PROFILE

Strong data-engineering experience in modern enterprise environments, with depth in data modelling, pipelines, integration, quality, lineage or governance topics
Able to operate across business needs, technical constraints and delivery realities
Strong SQL and practical understanding of data structures, transformations, traceability and controlled delivery environments
Comfortable working with multiple stakeholders across architecture, data, engineering and governance topics
Structured, pragmatic and able to take ownership of a defined subset of a broader senior data-engineering scope

SKILLS YOU'LL GROW

Broader exposure across the building blocks that make AI-ready data scalable in operation
Experience at the intersection of data engineering, integration, quality and delivery governance
Opportunity to deepen expertise in a specific component while contributing to a wider AI data foundation program

WHY JOIN / IMPACT

Work on data-engineering challenges directly tied to real AI deployment in Supply Chain
Role with enough breadth to offer variety while maintaining focused ownership within a defined perimeter
Help strengthen the data foundations that enable scalable AI delivery

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2d ago

Backend/AI Engineer

Left Main REI Charlotte, NC 🇺🇸 Remote

Charlotte, NC

2d ago

$100k - $140k/yr Full time Backend Developer Ai Workflows Amazon Web Services

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Job Description

Left Main REI is seeking a Backend/AI Engineer to design, build, and evolve backend services, data infrastructure, and GenAI-enabled features across Left Main products, with integrations to AWS, Snowflake, and Salesforce.

Responsibilities

Design, build, maintain, and optimize backend services and RESTful APIs that connect Left Main products with Salesforce, Snowflake, AWS, and external data providers.
Develop and operate serverless and cloud-native architectures using AWS services such as Lambda, API Gateway, S3, IAM, CloudWatch, EventBridge, and Kinesis.
Create robust data-processing pipelines for real estate data ingestion, enrichment, scoring, subscriptions, matching, deduplication, and delivery into customer-facing applications.
Design Snowflake-backed workflows with SQL transformations, stored procedures, Snowpark or Python processing, and performance tuning.
Architect and implement GenAI driven capabilities, including role-based agents, retrieval-augmented generation, prompt workflows, AI-assisted analysis, customer-facing copilots, and internal productivity tools.
Prototype new AI use cases, assess feasibility, and transition promising experiments into secure, reliable production services.
Collaborate with Salesforce engineers to define integration patterns using Platform Events, APIs, asynchronous processing, and precise data contracts across Salesforce, AWS, and Snowflake.
Support predictive and ML-enabled use cases such as lead scoring, buyer scoring, property intelligence, recommendation workflows, anomaly detection, and customer insights.
Enhance reliability, observability, and operational maturity across backend systems through structured logging, monitoring, alerting, automated tests, and clear incident response practices.
Contribute to CI/CD, infrastructure automation, environment management, and deployment practices for backend and data services.
Bring ideas, technical curiosity, and product-minded thinking to roadmap discussions, architecture reviews, and innovation planning.

Requirements

2+ years of professional backend engineering experience building production-grade APIs, services, data workflows, or cloud-native systems.
Strong hands-on experience with Python for backend development, scripting, automation, data processing, or AI/ML workflows.
Experience building RESTful APIs and integrating systems through APIs, webhooks, event-driven patterns, or message-based architectures.
Solid working knowledge of AWS, particularly serverless or cloud-native services such as Lambda, API Gateway, S3, IAM, CloudWatch, EventBridge, SQS, SNS, Kinesis, or similar.
Strong SQL skills and experience with modern data warehouses, preferably Snowflake.
Proven ability to design reliable, secure, observable, cost-conscious, and maintainable systems.
Familiarity with modern AI and GenAI development patterns, including LLM APIs, prompt engineering, RAG, embeddings, vector databases, model evaluation, agent workflows, or AI-assisted automation.
Ability to use contemporary AI development tools such as ChatGPT, Claude, Cursor, or GitHub Copilot to improve development speed, code quality, and documentation.
Experience with CI/CD pipelines, GitHub Actions, automated testing, infrastructure as code, or deployment automation.
Comfort working in a fast-moving startup environment where priorities evolve and engineers are expected to own outcomes beyond individual tickets.
Strong communication and collaboration skills to partner across product, engineering, data, Salesforce, and leadership teams.

Technologies

Python
AWS
Lambda
API Gateway
S3
IAM
CloudWatch
EventBridge
Kinesis
SQS
SNS
Snowflake
Snowpark
SQL
Salesforce
Salesforce Platform Events
GitHub Actions
GitHub Copilot
Cursor
ChatGPT
Claude
LLM APIs
prompt engineering
RAG
embeddings
vector databases

Benefits

401(k)
401(k) matching
Dental insurance
Flexible remote work arrangements
Life insurance
Paid time off
Vision insurance
Health insurance
Opportunities for professional growth and development
Collaborative and inclusive work culture
Salesforce certification incentives
Flexible schedule
Professional development assistance

Compensation

Salary range: USD 100,000 to 140,000 per year
Pay range: $100,000 - $140,000 per year
Generous benefits package
Paid holidays

Location and Work Arrangement

Location: Charlotte, NC, with remote work options

Work arrangement: Remote

Job type: Full-time

Licenses and Certifications

Salesforce Certification (Required)

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2d ago

Senior Data Analyst - Automation in Risk & Governance

Ally Financial Charlotte, NC

Charlotte, NC

2d ago

$85k - $150k/yr Full time Senior Analyst Analytics

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Job Description

Ally Financial offers a collaborative, impact-driven environment for data professionals focused on automation, governance, and risk management. This onsite role in Charlotte, NC combines hands-on tool development with data governance and reporting to support continuous monitoring. The position offers a salary range of USD 85,000 to 150,000 per year and requires a minimum of 3 years of experience, with a High School Diploma or GED as the educational baseline.

Benefits

Time Away
Planning for the Future
Health & Well-being
Building a Family
Work-Life Integration
Other compensations

The opportunity

Join Ally Financial as a Senior Data Analyst specializing in automation within risk and governance. You will work with advanced technology to support the development of premier risk management solutions, contributing to a team dedicated to precise and forward-thinking financial services.

Responsibilities

Design and sustain automated tools for assessing risk
Analyze complex data sets to identify potential risks
Collaborate with cross-functional teams to implement risk mitigation strategies
Uphold data governance standards across initiatives
Produce detailed reports and insights to guide decision-making
Create control testing automations in Snowflake to convert legacy processes into continuous monitoring
Leverage AI-assisted development workflows to speed automation delivery
Design retrieval systems to support control testing and operational decisions
Design and deploy user-driven workflows to automate tasks
Maintain Power BI dashboards to monitor automation health and control coverage
Develop Python scripts for automation pipelines and data transformations
Mentor junior teammates on technical development approaches
Document patterns and create playbooks for team replication

Requirements

3+ years of experience
High School Diploma or GED equivalent
More than 5 years of experience in data science, data engineering, or related technical positions
Strong command of SQL, with practical experience in Snowflake
Proficiency in Python for scripting and API integration
Experience with AI-assisted development tools and agentic coding workflows
Understanding of retrieval-augmented generation for building retrieval pipelines
Experience with Power BI for analytics and reporting solutions
Proven capability to convert manual processes to automated, scalable solutions
Ability to direct and support junior team members within a cooperative atmosphere
Entrepreneurial approach with strong written and verbal communication skills
Experience fine-tuning large language models for domain-specific applications
Familiarity with financial services, risk management, or compliance automation
Experience with continuous monitoring in a risk or controls environment
Proficiency with Streamlit for prototyping internal tools

Technologies

Snowflake
Power BI
Python
SQL
Streamlit

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2d ago

Lead Data Engineer

Daley and Associates Boston, MA

Boston, MA

2d ago

Full time Cloud Cloud Platform Data

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Job Description

Daley and Associates is seeking a Lead Data Engineer to own the development of data integration, dbt-driven data modeling in Snowflake, and the construction of end-to-end data pipelines that empower investment data analytics. This onsite role in Boston, MA requires a collaborative leader who can support the Investment Data Management Office three days per week while driving scalable solutions that align with architectural standards.

Responsibilities

Develop and maintain dbt models inside Snowflake, embedding business logic and ensuring alignment with the existing architecture and data standards.
Oversee and contribute to dbt projects, maintaining code quality, documentation, and modular, scalable design patterns.
Design, build, and administer scalable data pipelines and a robust data warehouse to support reporting, analytics, and operational use cases.
Lead development efforts and implement solutions that meet business requirements and support program objectives.
Drive continuous improvement of data quality, resiliency, control, efficiency, and monitoring capabilities.
Troubleshoot complex system interactions to identify root causes of issues.
Collaborate with the platform lead to design, develop, implement, and deploy new software components on the investment data platform.
Partner with the data architect to evaluate and finalize a unified data model.
Work with the integration architect to upgrade and integrate data ingestion and delivery tools within the unified platform.
Upgrade and integrate transformation, data validation, and orchestration tools to enable data engineering, analytics, and maintenance tasks.
Provide on-call support during unexpected outages.

Requirements

Bachelor’s degree in Computer Science or related disciplines.
5-6+ years designing, developing, and delivering data-centric, complex applications.
2-4+ years of hands-on work from SQL to Advanced SQL.
Experience developing and maintaining data models using dbt (Data Build Tool).
Background in data integration (ETL/ELT), data warehousing, analytics architecture, with familiarity in Snowflake and other cloud-native databases.
Development experience on cloud PAAS platforms such as Microsoft Azure, Google Cloud Platform, or Amazon Web Services.
Strong understanding of Agile SDLC, DevOps, and cloud technologies, with exposure to multiple technologies and environments.
Knowledge of architectures and patterns such as unified data management, data mesh, event-driven architectures, real-time data flows, non-relational repositories, and data virtualization.
Experience building solutions in the financial services domain with an understanding of financial instruments, transactions, and positions is desirable.
Solid interpersonal and communication skills with the ability to lead cross-team collaborations.

Technologies

dbt (Data Build Tool)
Snowflake
Microsoft Azure
Google Cloud Platform
Amazon Web Services

What we are looking for

Bachelor’s degree in Computer Science or related disciplines.
5-6+ years designing, developing, and delivering data-oriented, complex applications.
2-4+ years of progressive SQL experience, including advanced SQL.
Proven experience developing and maintaining data models with dbt.
Background in data integration (ETL/ELT), data warehousing, and analytics architecture; familiarity with Snowflake and other cloud-native databases.
Experience developing on cloud PAAS platforms such as Azure, GCP, or AWS.
Deep grasp of Agile SDLC, DevOps, and cloud technologies, with exposure to diverse technologies and environments.
Knowledge of unified data management, data mesh, event-driven, real-time data flows, and related architectures.
Experience in financial services data solutions, including instruments, transactions, and positions, is desirable.
Strong collaboration and communication skills to work across internal and external teams.

Preferred Qualifications

Experience in the asset management and investment data domain, including multi-asset platforms and related data ecosystems.
Understanding of asset management concepts and familiarity with various financial instruments and products.
Industry certifications in Snowflake, dbt, cloud data engineering, data warehousing, or financial markets are highly valued.
Interest in emerging AI technologies and how AI-driven tools can enhance engineering workflows, data quality, and analytics.
Familiarity with AI-assisted development, automation, or data engineering best practices to boost productivity.

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2d ago

Data Architect / Principal Data Engineer III

Hudson Manpower Cincinnati, OH

Cincinnati, OH

2d ago

$55 - $60/hr Full time Senior Cloud Cloud Platform

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Job Description

Senior-level Data Architect / Principal Data Engineer III responsible for designing and delivering scalable data solutions in a banking environment, onsite in Cincinnati, OH, with expertise in DBT, Snowflake, and SQL.

Responsibilities

Design, development, and support of data solutions, APIs, tools, and processes to enable rapid delivery of business capabilities.
Collaborate with IT application teams, enterprise architecture, infrastructure, information security, and line of business stakeholders to translate business and technical strategies into data driven banking solutions.
Serve as a technical expert addressing design, performance, integration, security, and related architecture challenges.
Pursue research and development on current trends and technologies related to banking, data engineering and architecture, data security, and related topics.
Work with developers to build CI/CD pipelines, self service build tools, and automated deployment processes.
Evaluate software products and provide documented recommendations as needed.
Provide support and troubleshooting for data platforms, with escalated on-call coverage for complex or critical incidents.
Participate in hardware and software planning activities.
Lead internal projects as needed, including legacy system replacements, monitoring and analytics improvements, tool development, and technical documentation.
Provide technical guidance and mentoring for other team members.
Manage and prioritize multiple assignments.

Requirements

Bachelor's degree in Computer Science, Information Systems, or an equivalent combination of education and experience.
Seven or more years of IT work experience relevant to the position.
Strong verbal and written communication skills, with the ability to tailor messaging for management, business sponsors, and IT stakeholders.
Working knowledge of application and data security concepts, best practices, and common vulnerabilities.
Experience in one or more of the following disciplines, preferred: big data technologies and distributions, metadata management products, commercial ETL tools, BI and reporting tools, messaging systems, data warehousing, Java, major version control systems, CI/CD tools, infrastructure automation and virtualization tools, major cloud platforms, or REST API design and development.
Previous experience working with offshore teams is desired.
Financial industry experience is a plus.

Technologies

DBT
Snowflake
SQL
Java

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance provided
401(k) with company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance available
Referral bonuses

Compensation

Hourly rate: USD 55 - 60

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3d ago

Data Engineer

SN Cloud Solutions Chicago, IL

Chicago, IL

3d ago

$0k+/yr Full time Python Apache Airflow Azure Data Factory

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Job Description

SN Cloud Solutions is seeking a Data Engineer to join its Chicago team in a hybrid arrangement. The role focuses on designing, building, and maintaining scalable data pipelines and data platforms that underpin enterprise analytics and BI, leveraging Python, PySpark, SQL, and cloud ETL/ELT tools. You will partner with data scientists, analysts, and business stakeholders to turn raw data into reliable insights.

Responsibilities

Architect and implement ETL/ELT pipelines for large-scale data processing.
Create scalable data solutions using Python, PySpark, and Apache Spark.
Build and sustain data ingestion frameworks for both structured and unstructured data.
Develop and tune SQL queries, stored procedures, and database objects.
Ingest and consolidate data from diverse sources, including APIs, databases, and cloud storage.
Establish data quality, validation, and monitoring mechanisms.
Deploy and operate on cloud platforms such as AWS, Azure, or GCP.
Create and manage data lakes and data warehouses.
Partner with data scientists, analysts, and business stakeholders.
Orchestrate workflows with tools such as Apache Airflow.
Diagnose production issues and optimize pipeline performance.
Follow Agile/Scrum practices and CI/CD processes.