Senior Data Analyst

Company Description Keansa Solutions - Global is a consulting and technology firm specializing in Enterprise Performance Management (EPM) and digital transformation. Founded in 2015 and headquartered in the Netherlands, the company serves clients across Europe, Asia Pacific, the UAE, and North America. Keansa helps organizations improve agility, performance, and profitability through analytics and planning, modern finance, S&OP, supply chain optimization, and ESG-focused initiatives. By combining deep domain expertise with leading technologies, Keansa delivers scalable, business-first solutions across industries such as Food & Beverage, Consumer Goods, Retail, Pharmaceuticals, and Energy. The organization is committed to turning uncertainty into clarity and enabling confident, data-driven decision making.

Role Description This is a full-time Senior Data Analyst role based in Singapore with a onsite work model. The Senior Data Analyst will collect, clean, and transform large data sets from multiple sources to support business performance and decision-making. This role will design and maintain data models, build analytical dashboards and reports, and perform advanced statistical and scenario-based analysis to support planning, forecasting, and operational insights. The selected individual will work closely with consulting, finance, operations and technology teams to translate business questions into clear analytical requirements and present findings in a concise, actionable format. Day-to-day responsibilities include documenting data processes, ensuring data quality, mentoring junior analysts, and contributing to continuous improvement of analytics practices and tools.

1.    Minimum 6+ years of hands-on experience working with data platforms (e.g., data warehouses, data lakes, cloud-based data solutions).

2.    Strong communication and interpersonal skills with demonstrated ability to manage and collaborate with business stakeholders at various levels.

3.    Solid understanding of data platforms, ETL/ELT processes, reporting tools, and dashboarding solutions (e.g., Power BI, Tableau, or similar).

4.    Strong finance domain knowledge, including familiarity with financial data structures, reporting requirements, and regulatory considerations.

5.    Proven experience in similar data analyst or data validation roles within data migration, implementation, or transformation projects.

1.    Experience with SQL, Python, or other data querying and scripting languages.

2.    Familiarity with data governance frameworks and data quality management practices.

3.    Bachelor's degree in Finance, Business Analytics, Computer Science, Information Systems, or a related field.

4.    Relevant certifications in data analytics, business intelligence, or cloud data platforms.