Local or 100% Remote About Point ✨ Real Impact, Real People: Our mission at Point is to make homeownership more valuable and accessible. Your work directly helps homeowners access their wealth, achieve financial flexibility, and realize life changing goals. ✨ Funding: With over $175M raised from top investors like Andreessen Horowitz, WestCap, Greylock, and Prudential, we’re scaling fast! You have the opportunity to join us at a pivotal stage. ✨ Game-changing Product: We're building a category defining company in home equity. We’ve earned a 4.7 Trustpilot rating and an A+ from the BBB, a testament to the value we provide to our 20,000+ customers. ✨ Great Place to Work: Our employees love working here! We are a Certified Great Place to Work and a Fortune Best Workplaces in the Bay Area. ✨ Remote First Culture, Genuine Connection: Work from anywhere in the U.S., while staying closely connected through virtual collaboration, team gatherings, and a people-first culture. About the role Point is looking for a Senior Data Engineer to join a lean, high-impact data team that powers analytics for 15+ business functions across a home equity investment company. You'll own the development and maintenance of a 1,600+ model dbt platform, build and optimize ETL pipelines in Airflow, manage Snowflake infrastructure (DDL deployments, permissioning, cost optimization), and ensure the reliability of 40+ data source integrations. This is a hands-on engineering role where your work directly shapes how the business makes decisions, and you'll also have the opportunity to contribute to emerging AI initiatives as the team expands into Cortex AI and LLM-powered workflows. Your responsibilities - Develop, maintain, and optimize dbt models across 20+ data marts serving business functions including marketing, production, servicing, finance, compliance, investor operations, and data science - Build and maintain ETL/ELT pipelines using Airflow (Astronomer), including custom operators, hooks, and sensors for data ingestion from 40+ sources - Manage Snowflake DDL deployments via schemachange — databases, schemas, warehouses, users, roles, network policies, integrations, and UDFs - Maintain and extend Terraform-managed RBAC grants (200+ .tf files), ensuring secure, auditable access provisioning across the Snowflake environment - Drive Snowflake cost optimization — warehouse sizing, multi-clustering configuration, query performance tuning, and monitoring to target 15–25% cost reduction - Support CI/CD pipelines for dbt Cloud, Astronomer deployments, and automated data quality testing - Develop and maintain AWS Lambda functions supporting data integrations, APIs, and serverless data processing workflows - Perform code reviews, enforce engineering standards, and contribute to data model documentation (YAML configs, markdown docs) across the platform - Collaborate with analysts and data scientists to build and maintain data marts, feature engineering tables, and semantic layer metrics that enable self-service analytics - Contribute to the team's AI/ML initiatives — including Cortex AI semantic models, data preparation for LLM workflows, and infrastructure supporting data science deployment pipelines About you - 5+ years of experience in data engineering or analytics engineering, with significant hands-on dbt and SQL development experience - Deep Snowflake expertise — DDL management, role-based access control, warehouse configuration, performance tuning, and cost optimization - Strong experience with Apache Airflow (or similar orchestration tools) — building DAGs, custom operators, scheduling, and failure handling - Proficiency in Python for data pipeline development, scripting, Lambda functions, and CI/CD automation - Experience with Infrastructure as Code — Terraform for access management, schemachange or Flyway for database migrations, version-controlled deployments - Solid understanding of data modeling — dimensional modeling, fact/dimension tables, data mart design, and enterprise data architecture - AWS experience — Lambda, S3, SAM/CloudFormation, and serverless architecture patterns - Strong Git workflows — branching strategies, pull request reviews, CI/CD integration (GitHub Actions or similar) - Excellent troubleshooting skills — ability to diagnose pipeline failures, data quality issues, and performance bottlenecks across a complex platform - Clear communicator — can work with non-technical stakeholders to translate business requirements into data models and explain technical tradeoffs Our benefits - Generous health benefits: We provide comprehensive medical, dental, and vision plans with options for flexible spending accounts (FSA) and health savings accounts (HSA). - Unlimited paid time off: Recharge with unlimited paid time off and 10 company holidays. - Flexible remote and onsite work: Our teams work from many different locations and time zones. We support fully remote work and also have an amazing in-person environment in our downtown Palo Alto, CA HQ. - Fully paid parental leave: Point will supplement state Paid Family Leave (PFL) so employees receive 100% of their regular base pay, plus two additional weeks of fully paid leave after state PFL ends. In states without PFL, Point offers up to 8 weeks of paid parental leave. In addition, employees also receive 4 weeks of fully paid transition time, during which you may work 2–3 days per week while receiving full base pay. - Equity: We offer meaningful equity because we believe in sharing the value you help create. Your contributions directly impact our growth, and your equity gives you a stake in our future success. - Financial wellness: We provide 401K retirement plans for employees as well as guaranteed life insurance and short- and long-term disability coverage. - Extra work/life benefits: We provide monthly stipends for internet, mobile plans, wellness perks, and a one-time home office reimbursement. Compensation at Point will be determined by skills, experience, and geographic location. Point has identified the expected annual base salary for this role at this level based on the market by tiers (Region | Location | Market Salary): - Tier 1 | San Francisco Bay Area, New York, and Seattle | $177,650 - $196,350 - Tier 2 | Chicago, Austin, Denver, Boston, Washington DC, San Diego, Portland, Sacramento, Philadelphia, Los Angeles & Santa Barbara | $161,500 - $178,500 - Tier 3 | All other US metro areas | $154,850 - $171,150 This does not include any other potential components of the compensation package, including equity, benefits, and perks outlined above. At the launch of each position, we benchmark compensation to the appropriate role and level utilizing competitive compensation data from various data sources as references. At the offer stage, we use the signal we received from our interviews, coupled with your experience, location, and other job-related factors, to determine final compensation. Location Requirement: This is a remote position. However, candidates must reside in one of Point’s states of operation: AL, AZ, AR, CA, CO, CT, DC, FL, GA, IL, KS, KY, MA, MD, MI, MN, MO, NH, NV, NJ, NY, NC, OH, OR, PA, SC, TN, TX, UT, VA, WA, WI. Point is proud to be an equal-opportunity employer. We provide employment opportunities regardless of age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. Each individual at Point brings their own perspectives, work experiences, lifestyles, and cultures with them, and we believe that a more diverse team creates more innovative products, provides better services to customers, and helps us all grow and learn. California Consumer Privacy Act Notice

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Senior Data Engineer, you will be instrumental in designing and building the next generation of our data infrastructure. Your work will handle massive volumes of behavioral, operational, and customer data, directly impacting product features like segmentation, personalization, and marketing effectiveness measurement across our entire MarTech SaaS offering. You will be a key technical leader, responsible for the architecture, reliability, and scalability of our core data assets. - This role moves beyond data transformation and focuses on architecture, optimization, and technical leadership. - Architect Scalable Systems: Design, develop, and maintain highly scalable, fault-tolerant, and performant ELT/ETL data pipelines using modern cloud data services to process billions of customer events daily. - Technical Leadership: Serve as a technical leader within the data team, defining data engineering standards, code review processes, and architectural best practices. Mentor junior and mid-level engineers on complex data challenges and best-in-class solutions. - Data Modeling & Optimization: Lead the design and implementation of optimized data models (e.g., Data Vault, Kimball, or other dimensional models) in our cloud data warehouse (e.g., Snowflake, BigQuery) to support real-time reporting, internal analytics, and machine learning initiatives. - Infrastructure as Code (IaC): Implement and manage data infrastructure using Terraform or CloudFormation to ensure reproducible and reliable deployment of data environments. - Ensure Data Quality & Governance: Establish advanced monitoring, alerting, and automated testing frameworks (e.g., dbt tests, Great Expectations) to enforce high standards of data quality, integrity, and regulatory compliance (GDPR, CCPA) across all data assets. - Cross-Functional Collaboration: Partner closely with Product Managers, Data Scientists, and Software Engineering teams to translate business requirements into robust, production-ready data solutions that power customer-facing features. Qualifications - 5+ years of professional experience in Data Engineering, focused on building large-scale, high-throughput data platforms. - Proficiency in SQL and extensive experience with modern cloud data warehouses (e.g., Snowflake, Databricks, BigQuery), including advanced concepts like performance tuning, clustering, and materialized views. - Deep expertise in Python for data engineering, specifically for building and optimizing complex data processing applications. - Proven experience with a modern data pipeline orchestration tool (e.g., Apache Airflow, Prefect, or Dagster) and data transformation tool (dbt). - Demonstrable experience with streaming data technologies (e.g., Apache Kafka, Kinesis, or Spark Streaming) to handle real-time customer engagement data. - Strong understanding of DataOps principles, CI/CD practices, and using Infrastructure as Code (IaC) tools. Requirements - Salary range: $108,400 — $135,500 USD. Benefits - A generous paid time off policy and a competitive benefits package that supports the health and well-being of you and your family. - Work flexibility with a hybrid work model combining remote work with access to office locations for collaboration and training.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description GHX is seeking a Software Engineer III to work on our Content Tooling solution with a focus on data engineering and analytics. This individual will be responsible for the creation, implementation, and support of data-intensive software solutions including complex SQL development, ETL pipelines, and analytics infrastructure. Reporting to the Manager, Software Engineering, the Software Engineer III will analyze, design, program, debug, and modify software enhancements and/or new products that process, transform, and deliver content data for business intelligence and operational reporting. This role is responsible for interacting with users to define system requirements and/or necessary modifications in an Agile/Scrum environment. Responsibilities - Design and implement complex SQL queries, stored procedures, and database optimization strategies - Develop and maintain ETL (Extract, Transform, Load) pipelines for data ingestion and transformation - Design and develop data architecture, data models, and data manipulation structures for content management systems - Build and optimize data warehousing solutions using cloud-based platforms - Create and maintain analytics reports and dashboards for business stakeholders - Perform data quality validation and implement data governance best practices - Translate ideas into clear, maintainable code with minimal supervision and perform code reviews - Coordinate with cross-functional teams including product, analytics, and offshore development teams in an Agile/Scrum environment Qualifications - Proficient with multiple technologies including SQL databases, ETL tools, cloud data platforms, and data visualization tools - Expert-level SQL development skills with deep understanding of query optimization and performance tuning - Strong understanding of ETL design patterns, data pipeline architectures, and data orchestration - Identifies, implements, and applies best practices for data engineering; is the “go to” person on the team - Ability to handle multiple projects and possesses a proven track record of high-quality deliverables - Delivers code with high quality and throughput consistently - Effectively communicates technical concepts to both technical staff and cross-functional teams with varying degrees of technical experience - Possesses a broad understanding of Agile/LEAN principles and ability to apply agile methodology effectively Requirements - Bachelor’s degree in Computer Science, Engineering, Data Science, or related degree - 5+ years of experience writing complex SQL queries including joins, subqueries, window functions, and CTEs with relational databases (PostgreSQL, MySQL, SQL Server) - 3+ years of experience designing and implementing ETL processes and data pipelines - Experience with data modeling (dimensional modeling, normalization/denormalization, star/snowflake schemas) and data transformation techniques - Experience with programming languages used in data engineering (Python, Java), version control systems (Git), CI/CD pipelines, and Agile/Scrum environments Preferred Experience - Hands-on experience with Snowflake data warehouse and Sigma Computing for building analytics reports and dashboards - Knowledge of healthcare supply chain or healthcare IT systems Benefits - Health, vision, and dental insurance - Accident and life insurance - 401k matching - Paid-time off - Education reimbursement Company Description Global Healthcare Exchange (GHX) enables better patient care and billions in savings for the healthcare community by maximizing automation, efficiency and accuracy of business processes. GHX is a healthcare business and data automation company, empowering healthcare organizations to enable better patient care and maximize industry savings using our world class cloud-based supply chain technology exchange platform, solutions, analytics and services. We bring together healthcare providers and manufacturers and distributors in North America and Europe - who rely on smart, secure healthcare-focused technology and comprehensive data to automate their business processes and make more informed decisions. It is our passion and vision for a more operationally efficient healthcare supply chain, helping organizations reduce - not shift - the cost of doing business, paving the way to delivering patient care more effectively. Together we take more than a billion dollars out of the cost of delivering healthcare every year. GHX is privately owned, operates in the United States, Canada and Europe, and employs more than 1000 people worldwide. Our corporate headquarters is in Colorado, with additional offices in Europe.

• Define the end-to-end data migration strategy from legacy systems to S/4HANA Public Cloud. • Lead the technical extraction from disparate, legacy ERP systems. • Utilize SAP S/4HANA Migration Cockpit and other SAP-native tools to ensure high-fidelity data loads. • Manage data cleansing and mapping to ensure the new S/4HANA environment remains ‘clean’ and performant.