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(Junior) Analytics Engineer - Job Opportunity at Gemma Analytics

Berlin, Germany
Full-time
Entry-level
Posted: June 9, 2025
Hybrid
EUR 45,000 - 60,000 annually for junior level in Berlin market, with potential for rapid growth given the company's profit-sharing model and the high demand for analytics engineering skills in the German market

Benefits

Team-focused events and cultural activities in Berlin fostering professional networking and team cohesion
Flexible work arrangements with 2-5 days office presence and workcation opportunities enabling optimal work-life balance
Premium equipment package including powerful laptops and multiple screens ensuring maximum productivity
Profit-sharing program distributing at least 20% of company profits to employees providing direct stake in company success
Comprehensive learning and development opportunities through meetups and lunch-and-learn sessions
Annual week-long company offsite combining team building with professional development
Honest and inclusive work environment prioritizing output over input hours

Key Responsibilities

Lead cross-functional collaboration with domain experts and business stakeholders to architect data solutions that directly impact business strategy and decision-making processes
Design and implement scalable data models and pipelines using cutting-edge technology stack, establishing the foundation for enterprise-level analytics infrastructure
Create executive-level reports and dashboards that provide actionable insights for strategic business decisions and performance optimization
Drive innovation through evaluation and implementation of modern data stack tools, positioning the organization at the forefront of analytics technology
Contribute to organizational knowledge sharing and mentoring culture while accelerating professional growth in a collaborative analytics engineering environment

Requirements

Education

A degree in Business, Economics, or a related field — or hands-on business experience in a commercial, marketing, product, or operations role OR a recent MBA or other advanced business training

Experience

First experience with SQL and relational databases

Required Skills

SQL and relational databases A curious, open mindset and the ability to think in both numbers and narratives Experience with a programming language (e.g. Python) Familiarity with BI tools like Power BI, Tableau, or Looker Experience managing stakeholders or cross-functional collaboration A basic understanding of data modeling techniques (e.g. Kimball or Data Vault) Business fluency in German and English (C1 or native level in both)
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Sauge AI Market Intelligence

Industry Trends

The analytics engineering role is experiencing explosive growth as organizations increasingly recognize the need for professionals who can bridge business requirements with technical implementation, creating a new category of data professionals that combines business acumen with technical expertise. Modern data stack adoption is accelerating rapidly, with companies moving away from traditional ETL approaches toward ELT, dbt, and cloud-native solutions, creating high demand for professionals who can navigate tool-agnostic environments and adapt to evolving technologies. European data privacy regulations and GDPR compliance requirements are driving demand for analytics engineers who understand both technical implementation and business context, particularly in German-speaking markets where regulatory expertise is increasingly valuable. The shift toward data democratization and self-service analytics is creating opportunities for analytics engineers who can build robust, user-friendly data infrastructure that empowers business users to generate their own insights.

Role Significance

Small collaborative team of approximately 20 professionals including data engineers, analysts, and consultants, providing extensive mentorship opportunities and direct exposure to senior-level decision making
Entry to junior level position with significant growth potential, designed as a launching pad for professionals transitioning from business roles into data or recent graduates seeking to combine business acumen with technical skills in a mentored environment

Key Projects

Implementation of end-to-end data pipelines for Series A startups establishing their first comprehensive analytics infrastructure Development of executive dashboards and KPI tracking systems for SMEs with 30-13,000 employees requiring scalable, maintainable solutions Cross-functional data architecture projects involving stakeholder management across multiple business units and technical teams Modern data stack tool evaluation and implementation projects that influence company-wide technology decisions

Success Factors

Strong business acumen combined with technical curiosity enables effective translation between business requirements and technical solutions, making the analytics engineer a critical bridge between stakeholders and implementation teams. Excellent communication skills and stakeholder management capabilities are essential for gathering requirements, managing expectations, and ensuring data solutions align with business objectives across diverse client organizations. Adaptability and continuous learning mindset are crucial given the rapidly evolving modern data stack and the company's tool-agnostic approach, requiring professionals who can quickly master new technologies and methodologies. Problem-solving orientation with ability to see patterns and ask the right questions transforms raw data into meaningful business insights that drive strategic decision-making.

Market Demand

Very high demand with limited supply of qualified candidates, as analytics engineering represents a relatively new discipline that requires a unique combination of business understanding and technical skills

Important Skills

Critical Skills

SQL and relational database expertise forms the foundation of all analytics engineering work, enabling data extraction, transformation, and modeling across diverse client environments and technology stacks. Business communication and stakeholder management skills are essential for success as analytics engineers must translate complex technical concepts into business value and gather requirements from non-technical stakeholders. Analytical thinking and pattern recognition capabilities enable analytics engineers to identify data opportunities, design effective solutions, and uncover insights that drive meaningful business outcomes.

Beneficial Skills

Python programming knowledge accelerates career growth by enabling advanced data manipulation, automation, and integration with modern data engineering tools and workflows. BI tool familiarity with platforms like Tableau, Power BI, or Looker enhances ability to create compelling visualizations and self-service analytics solutions for diverse client needs. German language proficiency opens additional market opportunities in the DACH region while English fluency enables international client engagement and career mobility.

Unique Aspects

Tool-agnostic approach providing exposure to the full spectrum of modern data stack technologies rather than being locked into specific vendor solutions, accelerating professional development and market versatility.
Direct client engagement from day one combined with structured mentorship creates an optimal learning environment that balances hands-on experience with professional guidance and support.
Profit-sharing model aligns employee success with company performance, creating entrepreneurial mindset and long-term career investment opportunities typically found in much larger organizations.
Focus on Series A to SME clients provides exposure to diverse business models and scaling challenges while avoiding the complexity and bureaucracy of enterprise-level implementations.

Career Growth

18-24 months to senior level given the mentorship structure and rapid company growth, with potential for management roles within 3-4 years

Potential Next Roles

Senior Analytics Engineer leading complex multi-client projects and mentoring junior team members Data Engineering Manager overseeing technical implementation across client engagements Principal Data Consultant managing strategic client relationships and architectural decisions Head of Analytics Engineering establishing best practices and technology standards

Company Overview

Gemma Analytics

Gemma Analytics operates as a profitable, bootstrapped consulting firm specializing in modern data infrastructure for startups and SMEs, distinguishing itself from VC-backed competitors through sustainable growth and client-focused service delivery since 2020.

Strong regional presence in the German-speaking market with over 50 successful client engagements, positioning the company as a trusted partner for data transformation initiatives among growth-stage companies.
Berlin-based with significant influence in the German startup ecosystem, leveraging the city's position as a major European tech hub to attract both talent and clients seeking modern data solutions.
Performance-oriented culture emphasizing work-life balance, continuous learning, and collaborative problem-solving, with profit-sharing demonstrating genuine commitment to employee success and long-term retention.
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