Data Analyst & QA Engineer

Data Analyst & QA Engineer at migx (Tbilisi). Deadline 03 August.

03 August MIGx is pleased to announce an opening for the position of Data Analyst & QA Engineer This Vacancy is onsite in Batumi or Tbilisi. About MIGx MIGx is a global consulting company with an exclusive focus on the healthcare and life science industries, with their particularly demanding requirements on quality and regulatory aspects. We have been managing challenges and solving problems for our clients in the areas of compliance, business processes and many others. MIGx interdisciplinary teams from Switzerland, Spain and Georgia have been taking care of projects in the fields of MCA, Integration, Application, Data Platforms, Processes, IT management, Digital transformation, Managed Services and compliance. About the profile: We`re looking for a Data Analyst and QA Engineer (Hybrid role) to join our Data and AI Engineering team. This role is ideal for those with a quality-first mindset - passionate about profiling, testing, and safeguarding the integrity of data, while also uncovering patterns that drive business decisions and turning validated data into clear, data-driven narratives. You`ll safeguard data quality across life sciences projects - profiling datasets, running structured tests, and documenting findings to an audit-ready standard — while also working with cross-functional teams to translate validated data into clear, evidence-based insights for technical and non-technical stakeholders alike. Responsibilities: ** Profile and analyze large datasets - assessing data quality (nulls, cardinality, distributions, uniqueness) and identifying trends, anomalies, and opportunities for optimization or improvement. ** Design, execute, and document structured test plans for data pipelines and dashboards, including defect tracking and reproducible results. ** Support data quality and governance initiatives by documenting data lineage, assumptions, methodologies, and incident write-ups with the traceability expected in a regulated environment. ** Build ETL pipelines and data transformations using Python to prepare and process structured and unstructured data. ** Perform exploratory data analysis (EDA) and statistical analysis using Python (pandas, NumPy, SciPy, scikit-learn). ** Collaborate with Data Engineers and Business Stakeholders to understand analytical requirements and translate them into technical specifications. ** Present findings and recommendations to technical and non-technical audiences with clarity and impact. ** Maintain dashboards and reusable data models in Power BI to support self-service reporting where needed. Requirements - Must have: What We`re Looking For: We`re committed to building a skilled and diverse engineering team. If you care deeply about writing clean code, delivering resilient systems, and collaborating across disciplines - this role is for you. Core Experiences & Skills: ** Data profiling: systematically assessing data quality across nulls, cardinality, distributions, min/max ranges, type consistency, and uniqueness. ** Test planning C execution: defining test scope, writing test cases traceable to acceptance criteria, tracking defects, and coordinating UAT/regression cycles. ** Strong documentation habits: process runbooks, incident write-ups, and analysis summaries, written with the traceability and version control expected in a regulated environment. ** Experience with SQL for querying and manipulating relational databases. ** Solid proficiency in Python for data analysis and manipulation (pandas, NumPy, matplotlib/seaborn), including exploratory data analysis and statistical techniques to uncover insights. ** Demonstrable data-driven mindset: ability to ask the right questions, validate assumptions, and support decisions with evidence. ** Working knowledge of Power BI for building or maintaining dashboards and reports. ** Understanding of data visualization principles and ability to communicate insights clearly to diverse audiences. ** Team-first mindset and experience in agile environments (Scrum or Kanban). ** Professional working proficiency in English (our internal and client-facing working language). Requirements - Nice to have: ** Experience with clinical trial data, healthcare analytics, or regulated industry datasets. ** Familiarity with advanced Python libraries (scikit-learn, stats models) for statistical modelling and machine learning. ** Knowledge of Git/version control for collaborative analytics projects. ** Experience with cloud platforms (Azure, AWS, or GCP) and cloud-native analytics tools such as Microsoft Fabric. ** Exposure to agile analytics methodologies or analytics engineering principles. ** Background with data governance, data quality frameworks, master data management, or GxP and other regulated industry standards. ** Exposure to QA testing practices and defect tracking tools (e.g. Jira, Azure DevOps), plus basic anomaly detection methods (e.g. z-scores, IQR) for flagging unexpected values. What we offer: ** Hybrid work model and flexible working schedule that suits night owls and early birds. ** 24 days of annual leave. ** Opportunities for career development and the opportunity to shape the company`s future. ** An employee-centric culture directly inspired by employee feedback - your voice is heard, and your perspective encouraged. ** Different training programs to support your personal and professional development. ** Work in a fast-growing, international company. ** Friendly atmosphere and supportive Management team. Address: Batumi, Tbel Abuseridze street 5-a. Tbilisi, Merab Kostava street, 37, Grato Passage.