Mindex

Engineer

• Serve as the Oracle CPQ technical expert for a client engagement, guiding solution design through implementation and deployment
• Partner directly with client stakeholders to understand business requirements, evaluate technical approaches, and recommend scalable Oracle CPQ solutions
• Design and configure Oracle CPQ functionality including pricing, subscriptions, Bill of Materials (BOM), Redwood UI, Rate Cards, and Approval Workflows
• Develop Oracle CPQ integrations using APIs to support AI-assisted quoting workflows and downstream business processes
• Analyze existing CPQ configurations, identify opportunities for improvement, and implement solutions that align with client business objectives
• Collaborate with architects, developers, business analysts, and client subject matter experts to ensure Oracle CPQ solutions integrate seamlessly within the broader application architecture
• Document solution designs, configuration decisions, and implementation approaches for both technical and business stakeholders
• Troubleshoot and resolve complex Oracle CPQ configuration, pricing, and integration issues throughout the engagement

Oracle CPQ Engineer

Platform Engineer

• Design, develop, and optimize Snowflake objects, including dynamic tables, views, and schemas
• Build and maintain DBT Core models, including models, tests, macros, sources, and lineage documentation
• Develop and support data ingestion and replication pipelines using tools such as Informatica, Fivetran, Openflow, or similar technologies
• Profile and analyze source data from complex, multi-domain systems to identify quality issues and inform modeling decisions
• Write advanced SQL to investigate data, validate transformations, and support business reporting and analytics needs
• Collaborate with data architects to implement canonical data models and ensure consistency across business domains

Data Platform Engineer

Data Engineer

• Design and implement scalable, high-performance data architectures across cloud and hybrid environments
• Define and enforce data modeling standards, including conceptual, logical, and physical data models
• Build and optimize enterprise data pipelines and data integration frameworks to support analytics and operational use cases
• Architect and manage data platforms leveraging technologies such as Snowflake, Databricks, Spark, and Azure Data services
• Collaborate with data engineers, data scientists, and business stakeholders to translate business needs into robust data solutions
• Establish and maintain data governance, data quality, and metadata management frameworks
• Ensure data privacy, security, and compliance requirements are met across all platforms and pipelines
• Lead architecture decisions for data storage solutions including data lakes, data warehouses, and real-time data processing systems
• Optimize performance and cost efficiency of data platforms and workloads
• Support Agile delivery frameworks and contribute to sprint planning, backlog grooming, and architectural roadmaps
• Implement and oversee CI/CD pipelines and infrastructure-as-code practices for data solutions
• Evaluate emerging technologies and recommend solutions to enhance data capabilities

Data Architect

• Assemble large, complex data sets that meet business requirements through extraction, transformation, and loading of data from a wide variety of data sources.
• Provide operational support and troubleshooting for existing processes and systems.
• Work closely with architects, solution leads, data owners, Data Scientists and key stakeholders to facilitate and coordinate the data platform backlog grooming process, triaging new feature requests in preparation for future project activities.
• Deliver automation & efficient processes to ensure high quality throughput & performance of the entire data & analytics platform.
• Ensure data extraction, transformation and loading data meet data security & compliance requirements.
• Engage with data source platform leads to gain tactical and strategic understanding of data sources required by Agency Data Services AI/ML as well as Data Office standards.
• Create data tools for data scientist team members that assist them in building and optimizing models.

Account Executive

• Prospecting and lead generation: Identifying potential customers and generating new leads through various channels, such as cold calling, email campaigns, networking, and referrals.
• Consultative selling: Understanding the customer's business needs and challenges to provide tailored cloud solutions that address their specific requirements.
• Product knowledge: Developing a deep understanding of the cloud-based products and services offered by the company, including features, benefits, and competitive advantages.
• Sales presentations and demonstrations: Delivering compelling sales presentations and conducting product demonstrations to showcase the value and capabilities of the cloud solutions being offered.
• Relationship building: Building strong relationships with customers and Cloud Partners like AWS and Azure, to establish rapport to gain trust and confidence in the company's cloud offerings.
• Negotiation and closing deals: Negotiating pricing, terms, and contracts to secure new business and close deals with customers, ensuring mutual satisfaction and meeting sales targets.
• Account management: Managing and nurturing existing customer accounts, identifying upselling and cross-selling opportunities, and ensuring customer satisfaction and retention.
• Market research and competition analysis: Keeping up-to-date with industry trends, market dynamics, and competitors to stay ahead in the cloud services market and provide insights for sales strategies.
• Collaboration: Collaborating with cross-functional teams, including marketing, product development, and customer support, to ensure a seamless customer experience and effective sales strategies.
• Sales reporting: Keeping accurate records of sales activities, customer interactions, and sales pipeline using CRM (Customer Relationship Management) tools, and providing regular reports to management.
• Achieve monthly sales quota.

AI & Cloud Sales Executive

• Identify and research target accounts across key industries aligned with Mindex’s growth goals
• Conduct outbound outreach via phone, email, and LinkedIn to decision-makers and influencers
• Manage high-volume prospecting and follow-up activities with a focus on quality conversations
• Nurture and qualify Marketing Qualified Leads (MQLs)
• Qualify opportunities by uncovering business needs, budget, authority, and timeline
• Schedule discovery and introductory meetings for the Sales team
• Learn and apply consultative selling techniques and value-based messaging
• Build working knowledge of Mindex’s cloud, data, and custom software solutions
• Partner with Sales, Marketing, and technical teams to support effective sales motions
• Maintain accurate CRM records of activity, conversations, and pipeline
• Track outreach activity metrics and assist with regular sales reporting
• Continuously refine prospecting and outreach strategies using data insights

Oracle CPQ Engineer

Data Platform Engineer

Data Architect

Data Engineer

AI & Cloud Sales Executive

AI & Cloud Outbound Sales Representative