Company Overview

The organisation operates in a data-driven business environment where accurate reporting, performance measurement, and analytical insights support strategic planning and operational decision-making. Its teams work with business data, reporting systems, and analytical tools to identify trends, understand performance, improve processes, and provide stakeholders with reliable information.

The organisation values analytical accuracy, structured problem-solving, data integrity, and clear communication. It encourages collaboration between analysts, technical teams, and business stakeholders to ensure that data is transformed into practical recommendations that support measurable business outcomes.

Role Summary

The Senior Data Analyst will lead analytical investigations, develop reliable reporting solutions, and translate complex datasets into actionable business insights. The position involves extracting and preparing data from multiple sources, identifying meaningful patterns, building performance dashboards, and communicating findings to stakeholders across different functions.

The successful candidate will combine strong SQL skills, statistical reasoning, business intelligence expertise, and a detailed understanding of data quality. The role requires the ability to work independently on analytical assignments, manage competing priorities, and ensure that reports and recommendations are accurate, relevant, and aligned with business objectives.

In addition to producing regular reports, the Senior Data Analyst will identify opportunities to improve analytical processes, establish consistent performance metrics, and support the development of self-service reporting capabilities. The candidate will also contribute to data governance practices and help colleagues interpret analytical results correctly.

Key Responsibilities

• Collect, extract, validate, and analyse data from databases, spreadsheets, business applications, and other approved information sources.
• Write and optimise SQL queries to retrieve, join, aggregate, and transform large datasets for reporting and analysis.
• Develop, maintain, and improve interactive dashboards and management reports using Power BI, Tableau, or comparable business intelligence platforms.
• Define and maintain key performance indicators, operational metrics, and reporting standards in collaboration with relevant stakeholders.
• Investigate changes in business performance by analysing historical trends, segmenting data, and identifying potential causes of significant variations.
• Conduct exploratory data analysis to identify patterns, anomalies, inefficiencies, and opportunities for operational improvement.
• Prepare recurring and ad hoc reports that provide reliable information for business planning, performance reviews, and management decisions.
• Build analytical datasets and reusable reporting models that improve consistency across departments and reduce duplicated reporting effort.
• Validate data completeness, accuracy, consistency, and timeliness before publishing reports or presenting findings.
• Investigate discrepancies between reporting systems, trace data-quality issues to their sources, and coordinate corrective action with technical teams.
• Apply appropriate statistical methods to compare performance, evaluate changes, and distinguish meaningful patterns from random variation.
• Translate complex analytical findings into concise reports, presentations, and recommendations suitable for technical and non-technical audiences.
• Work with business stakeholders to define analytical requirements, clarify reporting objectives, and establish appropriate success measures.
• Automate repetitive data extraction, transformation, validation, and reporting processes using SQL, Python, or available workflow tools.
• Document data definitions, calculation methods, assumptions, reporting logic, and dashboard usage instructions.
• Support data governance initiatives by promoting consistent definitions, controlled access, and responsible handling of business information.
• Review existing analytical processes and recommend improvements to reporting efficiency, data accessibility, and analytical accuracy.
• Collaborate with data engineers, software teams, and other analysts to improve data availability and the reliability of reporting pipelines.
• Present findings during business reviews and respond to follow-up questions about methodology, assumptions, and interpretation.
• Support junior analysts through knowledge sharing, peer reviews, and guidance on analytical techniques and reporting standards.

Requirements and Qualifications

• Bachelor’s degree in Data Analytics, Statistics, Mathematics, Economics, Computer Science, Business Analytics, or a related discipline; equivalent professional experience may also be considered.
• At least five years of experience in data analysis, business intelligence, reporting, or a closely related analytical role.
• Advanced SQL skills, including joins, common table expressions, aggregations, window functions, and query optimisation.
• Practical experience with Power BI, Tableau, or another established business intelligence and visualisation platform.
• Strong proficiency in Excel or comparable spreadsheet tools, including advanced formulas, pivot tables, and structured data analysis.
• Working knowledge of Python or R for data cleaning, exploratory analysis, automation, and statistical tasks.
• Understanding of descriptive statistics, sampling, correlation, hypothesis testing, and the limitations of observational data.
• Experience working with large datasets, multiple data sources, and structured reporting requirements.
• Ability to design dashboards that communicate trends and performance clearly without misleading visual representations.
• Familiarity with data warehouses, ETL/ELT processes, data modelling, and reporting data structures.
• Knowledge of data-quality validation, reconciliation, documentation, and basic data governance principles.
• Strong attention to detail and the ability to identify inconsistencies, question assumptions, and verify analytical results.
• Excellent written and verbal communication skills, with the ability to present findings to stakeholders with different levels of technical expertise.
• Strong organisational skills and the ability to manage multiple analytical requests in a remote working environment.
• Professional English proficiency and the ability to collaborate effectively with distributed teams.

Technical Environment

The role may involve SQL, Python, Excel, Power BI, Tableau, relational databases, cloud data warehouses, data transformation pipelines, and collaborative documentation tools. The successful candidate should be comfortable working across data extraction, preparation, visualisation, interpretation, and reporting.

Benefits

• Fully remote working arrangement within Estonia.
• Full-time, permanent employment structure.
• Opportunities to influence business decisions through high-quality analytical insights.
• Exposure to business intelligence, data modelling, reporting automation, and performance measurement.
• Collaboration with cross-functional teams and stakeholders.
• Opportunities for continuous professional development in analytics and data technologies.
• A professional environment that values data accuracy, accountability, and evidence-based decision-making.
• Opportunities to improve reporting processes and establish more effective analytical standards.

Application Instructions

Interested candidates should submit an up-to-date CV through the organisation’s designated application channel. Applications should outline relevant analytical experience, SQL proficiency, business intelligence tools, statistical knowledge, and examples of reporting or analytics projects.

Candidates may include a portfolio of dashboards, anonymised analytical case studies, or relevant code repositories where available. Please describe the business problem addressed, the analytical methods used, and how the findings supported a decision or improvement.

The recruitment process may include an initial CV review, an analytical interview, and a practical assessment involving SQL, data interpretation, dashboard design, or business problem-solving.

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