This page tracks remote data engineer openings that are location-eligible for Arizona.
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Defining what it means to build and deliver the most extraordinary sports & entertainment experiences.The Crown is Yours
At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It's transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We're not waiting for the future to arrive. We're shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. The Crown Is Yours As a Senior Data Engineer, Platform you will be a key contributor to a data team centered around the mission of providing a best-in-class experience for our products and customers. In this role, you'll be leveraging your technical expertise in all aspects of "Infrastructure as Code" (IaC) to enhance and build out our data platform. You will be working across teams, informing business decisions, helping to expand our platform, and define standards and best practices for platform use. What you'll do as a Senior Data Engineer, Platform - Demonstrate leadership and ownership of the platform to deliver services for projects and users. - Provide infrastructure guidance of data platform capabilities to accommodate business/technical use cases. - Leverage your strong communication skills to keep users informed and provide excellent quality of service. - Automate and manage provisioning needs, such as Snowflake storage and compute, Role Based Access Control model, and permissions. - Configure and manage monitoring/alerting around replication latency, performance (cluster & query), and Airflow. - Coordinate and collaborate with dependent infrastructure and AWS services to implement Snowflake integration with services, such as S3, IAM, SSO, etc. - Provide technical expertise, troubleshooting, and support for change management, governance compliance, internal audits, and remediations. What you'll bring: - A proven track record of administration, engineering, and operationalizing the Snowflake, Databricks or similar Cloud Data Platform. - Experience working in AWS, Terraform, CloudFormation, Python, and database replication tools/services (e.g., AWS DMS). - Experience working with CI/CD pipelines and deployment automation - Experience with a variety of data logging/monitoring tools, such as DataDog, - Strong experience with SQL and knowledge in a variety of data engines (for example, SQL Server, MySQL, Amazon Aurora, Redshift) is a big plus. - Experience writing software (preferably with Python) Join Our Team We're a publicly traded (NASDAQ: DKNG) technology company headquartered in Boston. As a regulated gaming company, you may be required to obtain a gaming license issued by the appropriate state agency as a condition of employment. Don't worry, we'll guide you through the process if this is relevant to your role. If this job posting does not include compensation information, this is due to a technical error that our team is working to resolve! We will repost this position with compensation information as soon as it is resolved. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
An online platform to test and advance your skills in penetration testing and cybersecurity. #ThinkOutsideTheBox
Role Description Let's redefine cyber security expertise standards and connect business - community through highly engaging hacking experiences. ✨The core mission of the Senior Data Engineer: - Own and evolve data pipelines on GCP. - Build new pipelines, harden existing ones, and improve data quality. - Make clean, trustworthy data available across the organization. - Work end-to-end on streaming and batch pipelines. - Design ELT/ETL processes on BigQuery and ClickHouse. - Build real-time pipelines on Pub/Sub and Kafka with Dataflow. - Orchestrate workflows with Airflow. - Ensure data is properly cleaned, modeled, and served for analytics, ML training, and online inference. - Partner with ML engineers on feature pipelines and monitoring data drift. - Consume and build REST APIs and integrate with third-party SaaS sources. - Treat infrastructure as code. Qualifications - Strong data modelling and warehouse architecture skills. - Hands-on experience with GCP data services. - Production experience with streaming pipelines. - Solid SQL and strong Python skills. - Experience with ClickHouse or another columnar OLAP engine. - Workflow orchestration experience with Airflow. - Comfortable with dbt or equivalent transformation frameworks. - Experience migrating off legacy warehouses onto cloud-native stacks is a plus. - Working knowledge of ML in production. - Docker & Kubernetes experience. - CI/CD mindset and infrastructure-as-code sensibility. Requirements - Design and build batch and streaming pipelines on Dataflow, Pub/Sub, and Kafka. - Drive the migration off Snowflake onto GCP-native stack. - Own the orchestration layer in Airflow. - Model data for analytics and ML. - Partner with ML engineers on feature stores and retraining workflows. - Capture requirements from stakeholders and translate them into data products. - Continuously improve data quality, reliability, observability, and cost efficiency. - Identify new data sources worth acquiring and integrate them cleanly. Benefits - Compensation: $140,000-160,000. - Medical, Dental & Vision (employee coverage 100% paid). - 401K with employer match. - Employer-paid Life and AD&D Insurance. - Supplemental Life Insurance. - Short-term and Long-term Disability. - Healthcare and Dependent Care FSA. - Paid parental leave. - 25 annual leave days. - Home Office Allowance. - Dedicated budget for training and professional development. - State-of-the-art equipment. - Full access to the Hack The Box lab offerings.
Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid. Project time expectations: Tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements; This is an estimate, not a guaranteed workload, and applies only while the project is active. Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.
Role Description Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system. In this role, as an AI Pilot – that’s how we refer to this role at Mindrift – you’ll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results. This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing. Key Responsibilities - Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets. - Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements. - Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior. - Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery. - Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes. Qualifications - At least 3 years of relevant experience in data engineering, web scraping, automation, or software development (required). - Bachelor's or Master’s Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus. - Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies. - Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML). - Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets). - Hands-on experience with LLMs and AI frameworks to enhance automation and problem-solving. - Strong attention to detail and commitment to data accuracy. - Self-directed work ethic with ability to troubleshoot independently. - A link to GitHub is a plus. - English proficiency: Upper-intermediate (B2) or above (required). Compensation On this project, contributors can earn up to $37 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements. Benefits - Work fully remote on your own schedule with just a laptop and stable internet connection. - Gain hands-on experience in a unique hybrid environment where human expertise and AI agents collaborate seamlessly — a distinctive skill set in a rapidly growing field. - Participate in performance-based bonus programs that reward high-quality work and consistent delivery.
We’re a publicly traded (NASDAQ: DKNG) technology company headquartered in Boston. As a regulated gaming company, you may be required to obtain a gaming license issued by the appropriate state agency as a condition of employment. Don’t worry, we’ll guide you through the process if this is relevant to your role.
Role Description As a Senior Data Engineer, Platform you will be a key contributor to a data team centered around the mission of providing a best-in-class experience for our products and customers. In this role, you’ll be leveraging your technical expertise in all aspects of “Infrastructure as Code” (IaC) to enhance and build out our data platform. You will be working across teams, informing business decisions, helping to expand our platform, and define standards and best practices for platform use. What you’ll do as a Senior Data Engineer, Platform: - Demonstrate leadership and ownership of the platform to deliver services for projects and users. - Provide infrastructure guidance of data platform capabilities to accommodate business/technical use cases. - Leverage your strong communication skills to keep users informed and provide excellent quality of service. - Automate and manage provisioning needs, such as Snowflake storage and compute, Role Based Access Control model, and permissions. - Configure and manage monitoring/alerting around replication latency, performance (cluster & query), and Airflow. - Coordinate and collaborate with dependent infrastructure and AWS services to implement Snowflake integration with services, such as S3, IAM, SSO, etc. - Provide technical expertise, troubleshooting, and support for change management, governance compliance, internal audits, and remediations. Qualifications - A proven track record of administration, engineering, and operationalizing the Snowflake, Databricks or similar Cloud Data Platform. - Experience working in AWS, Terraform, CloudFormation, Python, and database replication tools/services (e.g., AWS DMS). - Experience working with CI/CD pipelines and deployment automation. - Experience with a variety of data logging/monitoring tools, such as DataDog. - Strong experience with SQL and knowledge in a variety of data engines (for example, SQL Server, MySQL, Amazon Aurora, Redshift) is a big plus. - Experience writing software (preferably with Python). Company Description We’re a publicly traded (NASDAQ: DKNG) technology company headquartered in Boston. As a regulated gaming company, you may be required to obtain a gaming license issued by the appropriate state agency as a condition of employment. Don’t worry, we’ll guide you through the process if this is relevant to your role. If this job posting does not include compensation information, this is due to a technical error that our team is working to resolve! We will repost this position with compensation information as soon as it is resolved. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
• Owning the design and development of robust dbt Core models that transform raw data into trusted, analytics‑ready datasets in Snowflake • Architecting scalable, high‑performance data models that support enterprise reporting, analytics, and AI use cases • Translating complex business and analytical requirements into efficient, well‑structured ELT solutions through close collaboration with BI, analytics, and business stakeholders • Embedding best practices in data quality, testing, documentation, and lineage to ensure transparency, reliability, and trust in our data ecosystem • Leveraging Python to support automation, data validation, orchestration, and performance monitoring across ELT pipelines • Monitoring, tuning, and optimizing Snowflake query performance and cost efficiency • Leading technical design discussions and contributing hands‑on to critical data initiatives • Serving as a technical lead and mentor, guiding other engineers and elevating standards across the full data transformation lifecycle • Providing thought leadership on modern data transformation patterns, tooling, and architecture to help shape enterprise data strategy • Supporting data governance and metadata enrichment initiatives in alignment with broader enterprise data goals
GROPYUS is a technology-based construction company focused on building multi-story residential buildings. Thanks to its prefabricated building system with various design options, industrial offsite construction, and fully digitalized processes, the company manufactures aspirational, sustainable, and affordable homes using timber construction methods. GROPYUS is using scalable construction and manufacturing solutions to tap into a future market, boost Europe's strength in innovation, while also playing a substantial role in improving sustainability.
Role Description We are growing our Data Language Team within the Gropyus Tech department. The Language team is responsible for the semantic layer of our Gropyus Data Fabric as well as data modeling and transformation for our self-service analytics. Our team interacts with experts from various domains such as: - Digital Building Planning and Automation - Product Operations - Sustainability - AI - IoT - Construction engineers - Building architects - Logistics experts - Software engineering As part of the Data Language organization, you will: - Design data models to formalize concepts from various architecture and construction domains. - Contribute to the logic to transform and enrich our centralized data for self-service analytics. - Support Data Science use cases including Machine Learning and AI. - Collaborate with domain experts and software engineers to understand data needs and deliver high-quality datasets. - Implement and uphold data quality, governance, and security standards, including monitoring, testing, and documentation. - Adhere to best practices and rigor in development including documentation, data governance, testing, and validation. Qualifications - Experience working with a tech stack similar to: - Programming languages like Python or Kotlin - Query Languages like SPARQL, SQL - Data Reporting like PowerBI, Tableau, Quick Sight - Databases like Postgres, BigQuery, Spark, Graph DB - Cloud Storage Platforms - Ability to complete work as directed with guidance from senior engineers or leadership. - Experience resolving issues related to data discrepancies and inconsistencies and creating validation and testing for prevention and handling. - Data modeling experience through semantic or Business Intelligence development. - Experience following best practice guidelines in data and software engineering. Requirements - Some knowledge about semantic layer or ontologies (optional). - Experience with graph technologies and triples (optional). - Data Science, Machine Learning, and AI agents (optional). Benefits - Be part of something big: Join us in reinventing construction and sustainable, affordable living. - It’s on you: We offer a tremendous amount of ownership and room to make a mark at all organization levels. - Focus on results: You choose if you work from home, a park, or the office. - Bring your uniqueness to the team: Diversity in background, experience, and thinking is crucial to create the best product for everyone. - Be an owner: Participate in the success of GROPYUS through stock options.
Role Description You'll be the first person at LawnStarter dedicated to data governance - the owner of whether our data can be trusted. That means the quality and freshness of our source data, pipelines, and reports; the definitions behind our metrics; the standards behind our Segment event tracking; the health of our Lightdash workspace; the data feeding our machine learning models; and the security of the data itself. This is a hands-on role. You'll work solo at first, with the Analytics team around you but nobody under you - building automation, writing checks, fixing what's broken, and putting processes in place that scale past you. If the scope grows the way we expect, this becomes the foundation of a team you'd build. What makes this role different: - You're first. Governance has been everyone's side job, so what exists today is yours to reshape - keep what works, redesign what doesn't, and your standards become the company's standards. - Whole-stack ownership. Source data to pipelines to dashboards and ML models - you own trust across the entire chain, not one slice of it. - A live migration to shape. Lightdash is landing now. You get to set up its permissions, structure, and norms before bad habits form, instead of untangling them later. What You'll Own: - Data quality and freshness - automated monitoring across source data, pipelines, and reports; catching upstream schema and source changes before they break anything downstream; running incidents to resolution when they happen. - Data lineage and impact analysis - a living map from production source to warehouse model to dashboard, and the process that uses it: when a production change is proposed, its downstream impact on pipelines, metrics, and reports gets assessed before it ships, not discovered after. - Lightdash - administration, workspace structure, permissions, and the rollout itself. Your job is to give the company self-serve autonomy while keeping the workspace tidy enough that people can find and trust what's there. - The semantic layer - we just shipped it for our most critical metrics: one governed definition per metric, in code. You'll extend definition and mapping to the rest and guard the layer against uncontrolled growth as it scales. - Event tracking governance - our governed Segment event catalog: reviewing new events against its standards, keeping it matched to what production actually sends, and evolving the guardrails (naming, property dictionary, drift detection) as tracking grows. - AI data readiness - AI agents query our warehouse every day through Brain, our internal AI toolkit. You'll govern what data AI tools can access and keep the warehouse AI-legible: documented, consistent, and safe for an agent to query and get the right answer. - Data security and privacy - access controls, PII handling and retention under US state privacy laws, and periodic reviews of who - and which AI tools - can see what. - The governance system itself - the documentation, ownership models, and review loops that keep all of the above running without heroics. Qualifications - Governance is your craft, not your chore. You genuinely enjoy making data systems trustworthy and tidy. - AI-native. You use AI tools (Claude Code, Copilot, ChatGPT) daily to build quality checks, write automation, triage anomalies, and document as you go. - A hands-on senior operator. You write the SQL, debug the Airflow DAG, and configure the permissions yourself. - Automation-first. Your instinct for any recurring check is to build a monitor, not a checklist. - An enforcer people actually like. You'll hold engineers and analysts you don't manage to standards. Requirements - Zero pipeline incidents from unannounced source-data changes. - Zero freshness incidents - stakeholders never open a stale dashboard. - Every area of the business manages on official, well-maintained metrics and dashboards. - Every Segment event has an owner and a standard. - Governance runs as a system - documented processes that would survive you taking a month off. Benefits - Base salary: $75k–$100k/year - Equity: The whole company makes decisions on the data you'll guard. - Fully remote: This work needs deep focus, and we trust you to manage your environment. - Flexible PTO: We focus on results. Take what you need.
We're making driverless vehicles a safe, reliable, and accessible reality.
Role Description We are seeking a highly skilled and motivated Senior Data Analysis Engineer for our large-scale AI model and software evaluation framework – Ground Truth Regression. The ideal candidate will have a strong background in data engineering, machine learning principles, and statistical analysis. At Motional, large scale orchestration for data analysis plays a critical role in delivering our ML-centered autonomous driving vehicle. Our robo-taxi ML Models and software are developed by hundreds of developers and deployed multiple times a day. The Ground Truth Regression team provides the large scale perception analysis framework for validating all changes to perception which can impact the autonomous vehicle behavior. The GTRegression team validates the end impact of ML and software changes to the autonomous vehicle while those changes are in development, providing the tools for Root Cause Analysis and safety consideration. We monitor for model errors, anomalies, rare objects & long-tail driving scenarios across thousands of driving hours. The team develops the full stack – AWS Kubernetes orchestration framework, ReSimulation, model metrics, regression reports, and deep dive analysis UIs. The team works together with all other perception and ML teams to develop the metrics and analyze results. What You'll Do: - Work with ML Engineers and Autonomy Software Developers to develop new data analysis metrics and KPIs for the validation of the autonomous vehicle performance. - Drive innovation by researching and developing new large scale data analysis systems. - Own large-scale data analysis workflows that surface unexpected impacts of planned and unplanned changes to the ML models and software. - Build high-quality datasets to improve ML products through training & edge case validation. - Provide statistical depth on model performance & generalization through rigorous error and change analysis. Qualifications - Bachelor's or Master's degree in Computer Science, Data Science, or a related field. - Strong programming skills in Python, SciPy, and related data analysis frameworks. - Experience in machine learning, data mining, and statistical analysis. - Experience with large-scale data processing and distributed computing technologies. - Strong communication and software development skills: goal setting, design documentation, test frameworks, collaborative cross team development. Requirements - Ph.D. in Computer Science or a related field (Bonus Points). - Experience with cloud platforms such as AWS, Google Cloud, or Azure (Bonus Points). - Experience with machine learning in the autonomous driving domain (Bonus Points). - Publications or contributions to the AI/ML community (Bonus Points). Benefits - Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. Salary Range $159,000 — $207,000 USD Company Description Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more. - Our journey is always people first. - We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. - Our team is made up of engineers, researchers, innovators, dreamers, and doers, who are creating a technology with the potential to transform the way we move. - We’re creating first-of-its-kind technology that will transform transportation. - To do so successfully, we must design for everyone in our cities and on our roads. - We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. - Diversity helps us to see the world differently; it’s not only good for our business, it’s the right thing to do. - Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. - We’re driven to scale; we’re moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges. - Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. - Headquartered in Boston, Motional has operations in the U.S and Asia.
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• Design, build, and maintain automated data pipelines that move data from source systems (Salesforce, Xero, Ramp, product databases) into our central data lake and warehouses • Own the end-to-end data architecture, including storage strategy, processing systems, and pipeline orchestration • Implement and maintain ETL/ELT workflows that extract, transform, and load data into clean, analytics-ready formats • Partner with Data Insights Managers and business stakeholders to translate reporting requirements into robust technical data solutions • Build automated validation and quality-check layers into every pipeline to prevent bad data from reaching reporting layers • Monitor pipeline health in real time; triage and resolve failures quickly to meet data availability SLAs • Enforce data standards, naming conventions, schema consistency, and access controls across all systems • Support integration and maintenance of key tools including Salesforce, Xero, Ramp and Greenhouse into the data lake • Maintain auditability of all data flows and support compliance and governance requirements • Collaborate with the DIM TL and Director of Operations on the data roadmap and architectural decisions.
Hungryroot is the online grocery service that makes healthy eating easy and personal.
• Develop pipelines in Spark (Python) in the Databricks Platform • Build cross-functional working relationships with business partners in Food Analytics, Operations, Marketing, and Web/App Development teams to power pipeline development for the business • Ensure system reliability and performance • Deploy and maintain data pipelines in production • Set an example of code quality, data quality, and best practices • Work with Analysts and Data Engineers to enable high quality self-service analytics for all of Hungryroot • Investigate datasets to answer business questions, ensuring data quality and business assumptions are understood before deploying a pipeline
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Python, SQL, Airflow, AI/ML, Observability/Monitoring, AI
