Finance Business Intelligence and Data Specialist

Description

This Finance Data Specialist position is crucial for advancing data-driven decision-making within the finance department. This role bridges the gap between finance, operational units, and technology teams, requiring collaborative engagement to interpret business needs and develop effective data structures for business intelligence and data visualization solutions. The primary goal is to deliver timely, dependable, and accessible financial information, alongside practical insights, to facilitate significant business improvements and enhance the analysis of financial performance.

Responsibilities and Duties

- Participate in the creation and implementation of a strategic plan for financial data, its governance, and related analytics. - Engage with finance and business colleagues to understand operational logic, analytical requirements, and pinpoint relevant data measurements, with thorough documentation of these requirements. - Convert business needs into technical specifications and data requirements, combining business and financial data to establish a strong base for financial analysis and reporting tools. - Collaborate with operational teams and IT to conceptualize, define, and construct complete data pipelines for business intelligence tools, including the creation of instrumentation and definition of dimensional models, tables, or schemas that support business operations. - Support the ongoing development and upkeep of databases and data pipelines to guarantee data quality and availability for analysis. - Acquire data from a variety of sources (databases, APIs, web scraping, etc.), performing data cleansing and transformation into usable formats, resolving data quality issues such as missing information, aggregated figures, inconsistencies, and differing data formats. - Design, implement, and maintain data extraction, transformation, and loading (ETL) procedures for financial and operational data from diverse origins, providing valuable data insights to contribute to business success. - Conduct thorough examinations of financial data to discover trends and patterns, applying advanced analytical techniques to detect irregularities, exceptional cases, and discrepancies in transactions to minimize risks and maximize profits. - Work with stakeholders to determine key performance indicators and devise and suggest experimental approaches to consistently enhance analytical capabilities. - Maintain data integrity by performing data mining, cleansing, and analysis of substantial datasets to facilitate the effective creation of business intelligence and dashboard visualization systems. - Interpret analytical findings using a range of methods, from basic data summarization and statistical analysis to sophisticated data mining practices. - Create and refine financial reports and boost data automation to enable reliable self-service reporting and streamline the process of financial closing. - Employ business intelligence software to develop engaging data visualizations and dashboards that produce timely, pertinent, and actionable insights to inform crucial business decisions. - Construct predictive models to project future results based on past data, possibly using machine learning methods like regression, classification, and clustering. - Assist with projects and gather further data for specific analyses as required.

Qualifications and Requirements

- A bachelor’s degree in a relevant field such as Finance, Accounting, Business, Mathematics, Statistics, Economics, or Computer Science, or comparable professional experience and demonstrated proficiency. - Proven experience in financial data analysis, report automation, and business intelligence software. - A minimum of three to five years of experience in financial, business, or data analysis. - Prior experience in auditing or the logistics sector is a benefit. - A firm grasp of financial principles, data structures, and operational procedures. - Self-direction, proactivity, a focus on results, and the capability to handle multiple priorities. - The ability to work autonomously and manage tasks in less structured settings, with comfort navigating ambiguity. - Strong analytical abilities, intellectual curiosity, meticulousness, inventive thinking, and resourcefulness in solving problems. - Sound business judgment with the ability to synthesize complex data from various sources into relevant insights and actionable information for stakeholders. - Confidence and clarity in expressing well-reasoned challenges to business assumptions. - A focus on achieving both immediate and long-term objectives with a sense of personal responsibility. - Excellent communication and interpersonal skills in a diverse environment, with strong written and verbal English skills to effectively influence and motivate others. - A strong desire to learn and adapt to new tools, methods, and technologies in the field of data analytics. - Experience in developing and utilizing statistical and/or machine learning solutions to address business issues and create interactive data visualizations. - A solid understanding of the differences in data design between transactional ERP systems (e.g., SAP) and analytical data warehouses (e.g., Teradata, Snowflake). - Competence in data analysis tools (e.g., Excel, SQL) and business intelligence platforms (e.g., Power BI, Microsoft Fabric, Tableau). - Familiarity with scripting or programming languages (e.g., Python, R) for advanced analytical tasks.

Working Condition

Salary

Basic Salary 6000