• Develop scalable, automated data pipelines with CI/CD and Dataform in BigQuery for real-time player analytics • Design secure APIs to ingest external data into our Data Warehouse, ensuring reliable flows • Optimize data models in BigQuery and Datastream for fast queries and seamless integrations • Build ETL/reverse ETL pipelines using Google Dataflow for clean, high-quality transformations • Implement monitoring for data accuracy, consistency, and integrity across platforms • Uphold GDPR/CCPA compliance and data governance standards

About the Role We’re looking for a Senior Data Engineer to design, build, and optimize our data platforms so teams across the company can make fast, reliable, data-driven decisions. You’ll be a key technical leader, owning end-to-end data pipelines and modeling, and setting best practices around how we work with data. You’ll work heavily with Databricks, Spark, SQL, and Python, building scalable data solutions that power analytics, reporting, and data products. Experience in payments or financial services is a strong plus. What You’ll Do - Design and build data pipelines - Develop, maintain, and optimize ETL/ELT pipelines on Databricks and Spark. - Integrate data from multiple internal and external sources into a centralized data platform. - Own data modeling & architecture - Design and maintain robust data models (e.g., star/snowflake schemas, data vault, dimensional models) to support analytics and self-service BI. - Establish and enforce data modeling standards and documentation. - Ensure data quality, reliability, and performance - Implement data quality checks, validation frameworks, and monitoring. - Tune queries and jobs for performance and cost efficiency in Databricks and downstream systems. - Collaborate and lead - Partner with data analysts, data scientists, and product/engineering teams to understand data needs and translate them into technical solutions. - Provide technical leadership and mentorship to other data engineers; help review designs and code. - Governance & best practices - Contribute to and refine our data governance, security, and access control practices. - Drive best practices around version control, CI/CD for data, and code standards. Required Qualifications - 7+ years of professional experience as a Data Engineer, Software Engineer, or similar role. - Strong hands-on experience with Databricks (or a very similar cloud data platform) including cluster management, jobs, and notebooks. - Advanced experience with Apache Spark for batch and/or streaming data processing. - Expert-level SQL skills (complex joins, window functions, query optimization). - Strong Python skills for data engineering (e.g., PySpark, data processing libraries, scripting). - Proven experience in data modeling and designing schemas for analytics and reporting. - Experience building and maintaining data pipelines in a cloud environment (AWS, Azure, or GCP). - Strong understanding of data warehousing concepts, ETL/ELT best practices, and data lifecycle. - Solid software engineering fundamentals: version control (git), testing, code reviews, and CI/CD. - Excellent communication skills and the ability to collaborate with technical and non-technical stakeholders. Nice to Have - Experience in payments, fintech, banking, or broader financial services (e.g., transaction data, ledgers, risk, fraud, reconciliation). - Experience with streaming technologies (e.g., Spark Structured Streaming, Kafka, Kinesis, or similar). - Familiarity with dbt or similar transformations-as-code frameworks. - Experience with orchestration tools (e.g., Airflow, Databricks Workflows). - Knowledge of BI tools (e.g., Power BI, Tableau, Looker) and how data models power them. - Exposure to machine learning workflows and supporting data science teams. - Experience implementing data governance, lineage, and catalog tools. What You’ll Bring - A product mindset: you think about the end users of data and build with usability in mind. - A bias for automation, reliability, and scalability over one-off solutions. - Comfort with ambiguity, ownership of complex problems, and a desire to continuously improve the data ecosystem. What We Offer - 401k investment opportunity, with company match - Medical, Dental, and Vision Plans - Paid Time Off - Paid Parental Leave - Paid Volunteer Leave - Fully Remote Work environment Role Information: - Full-Time, Remote in the United States Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time. About Quilt Software Ever wondered how your favorite local shops compete with the big guys? That’s where we come in. We’re Quilt Software, providing Main Street's unsung heroes – from quirky cheese shops to family-run jewelry stores – with the tools they need to compete. Last year, we helped 14,000+ shops make over $2 billion in sales with our family of industry-specific software solutions.  If you get a kick out of supporting local businesses, love great software, and want to be part of a company that’s powering Main Street, we’d love to chat. Come join us in our quest to keep local retail not just alive, but thriving! Notice - Employment Scams Communication from our team regarding job opportunities will only be made by a Quilt Software employee with an @quiltsoftware.com email address. We do not conduct interviews over email or chat platforms, and we will never ask you to provide personal or financial information such as your mailing address, social security number, credit card numbers, or banking information. If you believe a scammer is contacting you, please mark the communication as "phishing" or “spam” and do not respond.

Job Summary Senior Data Engineer. Compass Group USA, Inc. 2400 Yorkmont Road, Charlotte, NC 28217. May telecommute (work from home) from anywhere in the US and report to Charlotte, NC company location. Build new pipelines in alignment with business needs for required projects and requests. Define, build, test, and implement scalable data pipelines using Python and SQL. Build stored procedures and views in Redshift and Snowflake. Work closely with Data Analytics and Reporting teams to align on strategy and to develop data models that feed business intelligence tools. Monitor legacy pipelines in production and monitor pipeline performance and efficiency. Improve efficiencies within existing data structures. Document new and existing data solutions. Interpret business requirements and design the best data solutions to meet them. Troubleshoot data related issues including missing data, poor data quality, etc. Maintain code via CI/CD process as defined in our Azure DevOps platform. Work M-F 9am – 5pm EST and overtime and weekends as needed to meet project deadlines and to ensure system stability. Work On Call production support 1 week out of every month. Salary: $145,314.00/year. Requires a Bachelor’s degree in Information Technology, Computer Engineering or related field or foreign equivalent. Requires two (2) years of data engineering experience to include two (2) years: SQL; Python; Extract, Transform, Load (ETL); Snowflake; Redshift; AWS Services. Apply: reference #118279. Any person may provide documentary evidence bearing on the application for permanent labor certification to Certifying Officer (CO), U.S. Department of Labor: U.S. DOL, ETA, Office of Foreign Labor Certification, 200 Constitution Avenue NW, Room N-5311, Washington, DC 20210. Compass Group USA

• Liderar la ejecución técnica y escalar la infraestructura de datos. • Actuar como mentor de un equipo de Data Engineers y Analytics Engineers. • Colaborar con equipos de pagos y atención al cliente. • Supervisar el ciclo de vida de la información desde la ingesta hasta el consumo. • Optimizar rendimiento y eficiencia de costos en el Data Warehouse. • Implementar políticas de gobierno de datos.