FP&A Analytics Engineer at Meltwater

What We're Looking For:


Meltwater is seeking an experienced Analytics Engineer to join our team and contribute to building a robust data infrastructure that supports financial planning and analysis initiatives.
This role will be based in our Cape Town office and report to the Senior Director of FP&A.
As an Analytics Engineer, you will play a key role in designing, building, and maintaining scalable data pipelines to transform raw data into actionable insights.
You'll collaborate closely with cross-functional teams to understand data requirements and leverage your expertise in modern cloud-based data platforms to implement robust ETL processes and enhance FP&A's data ecosystem developing and maintaining data models to support business intelligence, analytics, decision making and reporting needs. Your role combines rigorous analytics and data skills with the systems mindset needed for a modern, tech-driven FP&A team in SaaS.


What You'll Do:


Design, develop, and maintain scalable data pipelines and transformation workflows to integrate and unify financial, operational, and SaaS data sources using SQL, Snowflake, and ETL/ELT best practices.
Build and automate advanced financial models, forecasts, variance analyses, anomaly detection, and scenario planning tools that enable timely decision-making and enhance financial forecasting accuracy.
Collaborate cross-functionally with FP&A, Revenue Operations, and other teams to gather requirements and translate business needs into impactful data products and analytics solutions.
Create interactive dashboards and reports using BI tools (e.g., Power BI, Tableau) to deliver insights effectively for both technical and non-technical stakeholders.
Establish and maintain clear documentation, data quality standards, and governance protocols to ensure data integrity and analytics reliability.
Support FP&A team with financial reporting, budget tracking, KPI monitoring, and ad hoc analyses.
Drive continuous improvement of FP&A data infrastructure, analytics tools, and automated processes to optimize recurring financial data workflows.


What You'll Bring:

Required Qualifications


Bachelor's or Master's degree in Finance, Data Science, Computer Science, or a related field.
2 - 4 years of hands-on experience in data engineering, ETL development, and database management, with exposure to system architecture and data integration workflows.
Strong proficiency in SQL, experience working with modern ELT/ETL and reverse ETL tools such as Fivetran and DBT and orchestrators like Apache Airflow.
Familiarity with cloud platforms (AWS, Azure, or GCP) and data warehousing solutions such as Snowflake or BigQuery.
Strong problem-solving skills, attention to detail, and effective communication for cross-functional collaboration.


Preferred Qualifications


Understanding of SaaS and subscription-based business metrics (ARR, CAC, LTV, churn,etc.).
Experience working in FP&A or financial data modeling.
Knowledge of statistical analysis, predictive analytics, and data science programming
Techniques.
Experience with data visualization and BI tools (Tableau or Power BI).