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Data Analytics Analyst Poland Jobs

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Data Analyst (Commercial Data & Analytics)
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Join our team as a Data Analyst in Warsaw, focusing on Commercial Data & Analytics. You will develop data models, build automated workflows in Alteryx, and create dashboards in Tableau/Power BI. We seek a candidate with 3+ years' experience, proficiency in SQL, and strong analytical skills. We of...
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Poland , Warsaw
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Salary
128000.00 PLN / Year
https://www.baxter.com/ Logo
Baxter
Expiration Date
Until further notice
Data Analyst (Commercial Data & Analytics)
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Join our team as a Data Analyst in Warsaw, focusing on Commercial Data & Analytics. Utilize your 3+ years of experience and expertise in SQL, Alteryx, and Tableau/Power BI to build data models, automate pipelines, and create insightful dashboards. We offer a competitive salary, annual bonuses, pr...
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Location
Poland , Warsaw
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Salary
136000.00 PLN / Year
https://www.baxter.com/ Logo
Baxter
Expiration Date
Until further notice
Discover a world of opportunity in Data Analytics Analyst jobs, a dynamic and high-demand profession at the intersection of business, technology, and strategy. Data Analytics Analysts are the modern-day detectives of the corporate world, transforming raw, unstructured data into clear, actionable insights that drive smarter business decisions, optimize operations, and create a competitive edge. If you have a passion for problem-solving and a curiosity for what stories numbers can tell, a career as a Data Analytics Analyst offers a rewarding path. Professionals in these roles are typically responsible for the entire data lifecycle. A core part of their work involves data collection and management, where they gather information from various sources such as databases, CRM systems, and web analytics platforms. Following this, they perform data cleaning and transformation using ETL (Extract, Transform, Load) processes to ensure data accuracy and consistency for analysis. A significant portion of their day is dedicated to quantitative analysis, employing statistical techniques to identify trends, patterns, and correlations within large datasets. The ultimate goal is to translate these complex findings into digestible formats. This is achieved through data visualization, where analysts use tools like Tableau, Power BI, or Qlik to build interactive dashboards, reports, and charts that clearly communicate insights to stakeholders. They are also often involved in monitoring key performance indicators (KPIs) to track business health and support strategic planning. To succeed in Data Analytics Analyst jobs, a specific skill set is required. On the technical side, proficiency in SQL for querying databases is fundamental. Many roles also require knowledge of programming languages like Python or R for more advanced statistical analysis and data manipulation. A strong grasp of data visualization principles and hands-on experience with BI tools is essential for effective storytelling. Furthermore, understanding data warehousing concepts and ETL processes is highly valuable. Beyond technical prowess, soft skills are equally critical. These include analytical thinking to solve complex problems, meticulous attention to detail to ensure data integrity, and strong communication skills to articulate findings and their business implications to both technical and non-technical audiences. A logical and inquisitive mindset is the hallmark of a great analyst. Typical requirements for landing Data Analytics Analyst jobs often include a bachelor’s degree in a quantitative field such as Computer Science, Statistics, Economics, or Information Systems. While entry-level positions exist, many roles seek candidates with several years of hands-on experience in a data-centric environment. The profession offers immense versatility, with opportunities spanning across every industry from finance and healthcare to retail and technology. For those with a blend of technical expertise and business acumen, Data Analytics Analyst jobs represent a critical and future-proof career, empowering organizations to navigate the complexities of the digital age with data-driven confidence.

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