Customer Success Operations Engineer at Datacom

Christchurch, Canterbury, New Zealand -

Full Time

Start Date

Immediate

Expiry Date

03 Feb, 26

Salary

0.0

Posted On

05 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Python, SQL, Data Management, Automation, API Integrations, Data Visualization, Collaboration, Problem-Solving, Attention to Detail, Customer Focus, Emotional Intelligence, Business Acumen, Data Modeling, Workflow Optimization, Revenue Operations

Industry

IT Services and IT Consulting

Description

A bit about Smartly, a Datacom company We exist to make it simpler for Kiwi businesses to look after their people. We’re known as the simple way to sort your payroll for over 20,000 businesses. Our slick software combined with our awesome support team help businesses pay their people on time, accurately and in line with legislation. As a fast-growing FinTech expanding into adjacent markets, Smartly offers a fast paced, fun work environment with great opportunities for personal and professional development. What we’re looking for Data is at the heart of everything we do at Smartly: it starts with a deep understanding of our customers and our business and ends with leveraging the power of AI and machine learning, bringing it all together in innovative ways. Our Data & AI team partners deeply with teams across Smartly to ensure that our customers, our products, and our business have the models, data products, insights and automation they needed to make valuable decisions for our customers and our business. We’re looking for a Revenue Operations Engineer with a background in data engineering to optimize Smartly’s platform infrastructure that supports our revenue operations. Working closely with the Head of Revenue Operations, this role enables data-driven decision-making, automation of lead-to-revenue processes, and continuous improvements in revenue intelligence and forecasting. Additionally, the Revenue Operations Engineer collaborates with data engineering, platform owners, and cross-functional teams to enhance Smartly’s revenue tech stack and drive operational efficiencies. By aligning revenue operations technology, automation, and analytics, this role ensures that sales, marketing, customer success, and finance teams have the tools, insights, and systems needed to drive revenue growth What You'll Do Revenue Data Management & Process Optimization: Collaborate with data engineering and data analytics to build and manage data pipelines to integrate revenue data from HubSpot, Zuora, and other business systems Drive the creation of processes to transform and structure revenue data for analytics and reporting. Implement data cleansing, normalization, and enrichment strategies to ensure revenue data quality and governance. Automate revenue reporting and forecasting by integrating data sources into a unified analytics framework. Support revenue analytics initiatives by designing data models for pipeline, customer lifecycle, and revenue trends Revenue Automation: Collaborate with platform owners, e.g. HubSpot and Zuora, to implement processes and workflows that deliver productivity and efficiency gains for Smartly Leverage data to develop workflow automation within HubSpot and Zuora to streamline lead -to -revenue processes across relevant revenue generating business functions, e.g. reduce and or automate handoffs between teams, identify signals for churn reduction. Implement automation to improve data entry, validation, and workflow consistency Ensure that the revenue tech stack integrations (HubSpot, Zuora, and other revenue and analytics platforms) are synchronized and optimized for accuracy Revenue Technology & Platform Optimization: Collaborate with platform owners to improve system integrations and workflow efficiency. Collaborate with the Product and Engineering team to implement API -driven integrations between revenue platforms and Smartly’s product ecosystem. Collaborate with data engineers and data scientists to enable real -time revenue analytics and dashboards, enabling business teams to track pipeline health, conversion rates, and revenue KPIs. Implement A/B testing for process changes, measuring impact on revenue efficiency and deal velocity. Monitor revenue operations system performance, data synchronization issues, and automation failures, troubleshooting as needed. Cross Functional Collaboration: Work closely with data and business teams to align on revenue data solutions needs Collaborate with Sales, Marketing, Customer Success and Finance to improve revenue data flows, automation, and reporting accuracy. Act as a bridge between technical and business stakeholders, translating revenue operations needs into scalable system solutions. Other Duties: Carry out other duties as required from time to time Experience and Qualifications: Bachelor’s degree in a relevant field such as Data, Engineering, Statistics, or a related quantitative field. Demonstrable track record delivering complex data engineering and analytics projects successfully Technical Expertise: Proficient in Python and SQL for data handling; advanced Excel skills (e.g., formulas, pivot tables, macros). Working knowledge of cloud platforms. Data Management: Experience in data cleaning, transformation, validation, and reporting. Customer Tech Stack/Revenue Operations Platforms: CRM & Billing Systems knowledge is a bonus. System Integrations & APIs: Familiarity integrating revenue platforms using API calls, middleware, or no-code automation tools (e.g., n8n, Zapier) is also a bonus. Data Visualization: Experience in producing data visualization solutions using tools like Power BI or similar platforms. Strong data presentation, visualization and report writing skills. Communication Skills: Strong ability to explain complex data processes to nontechnical stakeholders. • Problem-Solving: Aptitude for identifying and resolving data-related issues efficiently. Attention to Detail: Meticulous in ensuring data accuracy and consistency. Strong customer focus, emotional intelligence and business acumen. Experience and proficiency sourcing, validating and documenting requirements. Experience and Skills: Data engineering expertise: Solid understanding of data engineering fundamentals and concepts. Familiarity with orchestration, ingestion, and transformation of multisource datasets. Data modelling: Solid understanding of data modelling for analytics purposes. Collaboration and teamwork: You'll thrive working a wide community of business and technical stakeholders to drive projects forward. Comfortable working independently as well as closely collaborating across functions to identify problems and deliver high quality solutions with business and technical rigor Key Competencies: Fresh thinking - committed to continuous improvement and develops innovative and creative solutions that add value to Smartly, and its customers. Positive with ability to thrive in a constantly changing environment. Quality Driven - Is guided by principles and values and acts with integrity to deliver superior outcomes. Organized and results oriented – efficient time management skills and can-do attitude. Open and Honest - Openly shares knowledge, sets expectations, provides meaningful advice, and gives and receives constructive feedback with all stakeholders. Proactive – demonstrates strong initiative & comfortable with a high level of autonomy. Self-management - Effectively manages the responsibilities and objectives of their role. Adapts to innovation and improved ways of working

Responsibilities

The Customer Success Operations Engineer will optimize Smartly’s platform infrastructure to support revenue operations, enabling data-driven decision-making and automation of lead-to-revenue processes. This role involves collaborating with various teams to enhance the revenue tech stack and drive operational efficiencies.