Middle Data Analyst

Nextchallenge; Polska; Remote; PLN 80,000 - 110,000; Full time

Benefits offered by this job

Flexible working hours

Remote working options

Vacation policy

Professional development allowances

Health insurance

Referral program

Job summary

Nextchallenge is seeking an experienced Middle Data Analyst to drive data-informed decisions in the iGaming analytics team. You will own complex SQL workflows in Redshift, analyze player behaviour, and deliver concise outputs for non-technical stakeholders.

Collaboration across functions and ongoing adoption of AI tools are key parts of the role. You will work with BI dashboards, Excel-based reporting, and onboarding tasks like EasyMorph for data preparation.

Qualifications

• 3–4 years of hands-on experience as a Data Analyst in iGaming or online gambling.
• Advanced SQL in Amazon Redshift with window functions and large data sets.
• Experience with BI tools (Power BI, Tableau, Looker) for dashboards.

Responsibilities

• Design and own end-to-end analytical workflows in Amazon Redshift.
• Conduct deep-dive player behaviour analyses: segmentation, cohorts, LTV forecasting.
• Analyse A/B test results and present actionable recommendations to stakeholders.
• Track iGaming KPIs such as GGR, NGR, and churn; flag anomalies.
• Integrate AI tools into daily analytics: prompt engineering, AI-assisted SQL.
• Translate data findings into clear Excel reports and presentations.
• Learn and use EasyMorph for reporting and data prep tasks.

Skills

Amazon Redshift

SQL

Player analytics

A/B testing

BI tools

Excel

LTV forecasting

Churn analysis

AI in analytics

Data quality

English

Tools

Amazon Redshift

Power BI

Tableau

Looker

Excel

EasyMorph

Amazon QuickSight

Job description

We’re looking for an experienced Middle Data Analyst to join the analytics team in the iGaming industry. You’ll take ownership of complex analytical tasks, drive data- informed decisions across multiple business functions, and serve as a go-to expert for data quality, player behaviour analytics, and reporting. If you have a solid background in gambling analytics and love working with large datasets, we want to hear from you.

Key Responsibilities:

• Design and own end-to-end analytical workflows in Amazon Redshift — complex multi-step SQL: window functions, CTEs, large-scale joins, and performance tuning;
• Conduct deep-dive player behaviour analyses: segmentation, RFM modelling, cohort analysis, LTV forecasting, and churn prediction;
• Analyse A/B test results — interpret statistical significance, evaluate group comparability, identify confounding factors, and deliver clear recommendations to stakeholders;
• Track and analyse iGaming KPIs — GGR, NGR, bonus abuse index, deposit/withdrawal trends, player LTV, and churn — proactively flagging anomalies;
• Integrate and actively apply AI tools into day-to-day analytical work: prompt engineering, AI-assisted SQL generation, automated insight summarisation;
• Translate complex data findings into clear, actionable outputs for non- technical stakeholders via Excel reports and presentations;
• Learn and work in EasyMorph for reporting and data preparation tasks as part of team onboarding.

Required Skills & Experience:

Technical skills:

• 3–4 years of hands-on experience as a Data Analyst in iGaming or online gambling — mandatory;
• Advanced SQL in Amazon Redshift — window functions, CTEs, subqueries, query optimisation, and working with large-scale datasets;
• Experience with BI tools (Power BI, Tableau, Looker, or similar) — working with dashboards and using them to extract insights;
• Proficiency in Excel: advanced pivot tables, VLOOKUPs, and executive-level reporting;
• Strong command of iGaming KPIs: GGR, NGR, player LTV, churn rate, bonus abuse metrics, deposit/withdrawal volumes;
• Solid understanding of A/B test analysis — interpreting p-values, confidence intervals, and effect sizes; experience evaluating pre-test group balance and flagging randomisation issues;
• Practical use of AI tools in analytical workflows: LLMs for insight generation, AI-assisted querying, prompt engineering for data tasks;
• Strong data quality mindset — ability to sense-check numbers, investigate inconsistencies, and ensure analytical accuracy;
• Clear English communication, written and verbal (upper-intermediate+).

Nice to Have:

• Familiarity with Amazon QuickSight: navigating dashboards, using built-in features (Q / flow), filters, and calculated fields;
• Exposure to EasyMorph or similar ETL/data preparation platforms.

Soft Skills:

• High ownership and autonomy — you manage your tasks end-to-end without hand-holding;
• Structured analytical thinking — you break down ambiguous business questions into clear data problems;
• Proactive communication — flagging anomalies, pushing back on flawed assumptions, and keeping stakeholders aligned;
• Ability to manage multiple priorities and deliver under deadlines in a fast-paced environment;
• Collaborative mindset — comfortable working across teams and supporting junior colleagues.

The company guarantees you the following benefits:

• A positive workplace atmosphere that creates a culture of collaboration and support, making it a place you'll love working in;
• Competitive compensation and regular career development reviews;
• Flexible working hours and remote working options, you'll enjoy the freedom that the company provides;
• A generous vacation and sick leave policy, allowing you to take time off and enjoy a work-life balance;
• Financial assistance for professional development, helping you stay ahead of the curve and love your career path;
• Educational Allowances that give you the opportunity to expand your knowledge and experience;
• You'll have a monthly allowance for personal activities, giving you the opportunity to pursue your interests and hobbies outside of work;
• A comprehensive health insurance plan, depending on your current location;
• Referral program with financial rewards for bringing top talent to the company;
• Engaging in team-building activities and corporate parties.
• HR Interview with the Recruiter;
• 30-minute technical interview;
• 1.5-hour Final interview with the team;