DATA OPERATIONS ANALYST
OVERVIEW
We are looking for a Data Operations Analyst to support ongoing data quality, governance, and systems integration initiatives across Salesforce, NetSuite, and our wider enterprise system landscape.
This role is ideal for someone with strong Salesforce fluency — ideally from a SalesOps, RevOps, or Sales Systems background — who understands how a SaaS sales lifecycle plays out in CRM data, and who brings a genuine appetite for growing into data quality and governance work. Deep SQL or ETL experience is not required; we'll build that together.
We are a small, ambitious team modernising our tooling and ways of working — and we want someone who is curious, collaborative, and excited to grow with us.
We actively welcome new ideas — technical or otherwise. If you have a better way of doing something, we want to hear it. Innovation is not reserved for product teams; it is part of how we operate day to day, and we want someone who thinks that way too.
The position will focus on data quality reporting and remediation across our CRM and ERP platforms, while also supporting data governance activities, cross-system integration monitoring, and the team's broader platform modernisation agenda.
What You'll Do
Data Integrity
- Building reporting capabilities to identify data quality issues, developing measurements, and tracking improvements in data health over time.
- Profiling databases, identifying and interpreting trends or patterns in complex data sets, and distinguishing isolated errors from systemic issues.
- Diagnosing root causes of data quality failures, planning and executing remediation strategies, and monitoring for recurrence.
Data Governance & Standards
- Supporting the implementation and maintenance of a business data dictionary and data standards framework.
- Gathering requirements from business stakeholders for data standards and quality definitions.
- Helping document processes, standards, and remediation approaches clearly for both technical and non-technical audiences.
Systems Integration & Reliability
- Monitoring data flows across connected systems — Salesforce, NetSuite, Gainsight, Zendesk, and Partner Portal — and troubleshooting integration issues.
- Supporting scheduled cross-system reconciliation to ensure data consistency across platforms.
- Evaluating changes to source systems for their downstream data quality impact.
Platform Modernisation & Technical Growth
- Contributing to the team's tooling and process evolution — actively exploring new and better ways of doing things, whether that's a smarter approach to a recurring task, a new tool worth evaluating, or a method the team hasn't tried yet.
- Actively developing SQL and Python skills through structured learning (Coursera courses are available) and applying them in day-to-day work.
- Adopting AI tools (including Claude) to improve productivity in documentation, analysis, and knowledge capture — in line with Mimecast's AI adoption agenda.
Stakeholder Data Services
- Supporting internal stakeholders across Sales, Finance, Marketing, and Partners with data requests, analysis, and remediation.
- Providing quality assurance of imported data and supporting UAT, system migrations, and data-related project implementations.
- Participating in continuous improvement — identifying process gaps and opportunities to improve data reliability and operational efficiency.
KEY RESPONSIBILITIES
- Build and maintain reporting capabilities that identify data quality issues across CRM, ERP, and other enterprise systems
- Extract, profile, and analyse data across Salesforce, NetSuite, and connected platforms — using Salesforce reporting tools day one, and building toward SQL over time
- Use ETL tools to extract and transform data from business systems for analysis and remediation
- Perform data profiling to establish baselines and surface anomalies
- Diagnose root causes of data quality issues and trace them back to source systems, integrations, or process gaps
- Plan and execute remediation strategies, then monitor for recurrent events to confirm fixes have held
- Support cross-system reconciliation work, including ID and field agreement checks between Salesforce and connected systems
- Evaluate changes and updates to source production systems for their downstream impact on data quality
- Gather requirements from business stakeholders for data standards and project implementations
- Support the implementation and ongoing maintenance of a business data dictionary
- Develop measurements and reports, and track improvements in data cleanliness over time
- Monitor systems on an ongoing basis to ensure data remains aligned to business requirements
- Document findings, data standards, and remediation approaches clearly, and present recommendations to stakeholders
- Actively engage with AI tools to improve team productivity in documentation, analysis, and day-to-day tasks
- Complete structured Python and SQL training and apply those skills in live work
- Bring ideas — challenge how things are done, propose improvements, and contribute to the team's culture of continuous innovation
What You'll Bring
- 3+ years of experience in a data analysis, data quality, or data operations role
- Demonstrable SQL and / or Alteryx skills — comfortable writing queries to extract, filter, join, and profile data
- Experience with Salesforce as a data source — understanding of object structure and data relationships
- Strong understanding of database concepts: entities, attributes, constraints, relationships, and joins
- Ability to identify data quality issues, diagnose root causes, and drive remediation through to resolution
- Ability to manage multiple priorities across concurrent data quality initiatives
- Analytical mindset with strong logic-building, research, and attention to detail
- Strong communication skills — able to work effectively with both business users and technical teams
- Comfortable operating in a small team with broad responsibilities and a collaborative working style
- Genuine curiosity and appetite for technical growth — willing to learn new tools and methods on the job
- An innovative mindset — someone who spots a better way and says so, rather than accepting the status quo
Bonus Skills (Not Essential)
- Demonstrable SQL and / or Alteryx skills — comfortable writing queries to extract, filter, join, and profile data
- Experience with NetSuite or other ERP platforms from a data quality perspective
- Exposure to Python — even basic scripting or automation experience
- Familiarity with Snowflake or other cloud data warehouse environments
- Experience with ETL tools such as Alteryx, Boomi, or similar middleware
- Exposure to BI reporting tools such as Power BI, Tableau, or Streamlit
- Understanding of API-based integrations and the data quality implications of system-to-system data flows
- Experience with AI tools (Claude, Copilot, or similar) in a professional context
- Experience supporting data governance initiatives — data dictionaries, data standards, or master data management
- Experience creating documentation, knowledge articles, and data standard definitions
- Experience supporting UAT, system migrations, or data-related project implementations
- Exposure to CPQ, quote-to-cash, or finance data models within Salesforce or NetSuite
The Ideal Candidate
You know Salesforce inside out — how the objects connect, how a deal flows from lead to renewal, and where the data tends to break along the way. You understand business impact, communicate clearly with stakeholders, and take ownership of problems through to resolution.
But just as importantly, you are someone who wants to grow. We are a team in transition — modernising our tooling, building new skills, and raising our ambition for what data operations can deliver at Mimecast. We want someone who is excited by that direction, not intimidated by it.
We want an innovator. Not necessarily someone with a technical invention to their name — innovation here means noticing a better way, being willing to say so, and caring enough to help make it happen. Whether that is a smarter approach to a recurring data problem, a new tool worth trying, or a process improvement nobody has got around to suggesting yet — we want someone who brings that energy to the team.
You will be joining a small, experienced team recovering from a demanding delivery period. We value collaboration, intellectual curiosity, a positive attitude, and someone who makes the people around them better — as much as we value technical skill.
If you are passionate about data, genuinely curious about where data and AI are heading, and want to work on data that actually matters to a growing business — we would love to hear from you.
The base salary range for this position is 440,000−660,000 ZAR plus benefits. This range represents the minimum and maximum new hire compensation for this role. The position may also be eligible for incentive plans and additional benefits, in accordance with company policy and local regulations. Our salary ranges are determined by role, level, and location with individual compensation also dependent on factors such as qualifications, experience, and skills. Final offers will reflect these considerations and may vary accordingly.
Belonging at Mimecast
Cybersecurity is a community effort. That’s why we’re committed to building an inclusive, diverse community that celebrates and welcomes everyone – unless they’re a cybercriminal, of course.
We’re proud to be an Equal Opportunity and Affirmative Action Employer, and we’d encourage you to join us whatever your background. We particularly welcome applicants from traditionally underrepresented groups.
We consider everyone equally: your race, age, religion, sexual orientation, gender identity, ability, marital status, nationality, or any other protected characteristic won’t affect your application.
Due to certain obligations to our customers, an offer of employment will be subject to your successful completion of applicable background checks, conducted in accordance with local law.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.
