About The Role
As an Analytics Engineer, you will act as the bridge between raw data and business insights. You'll create the systems that empower our data teams, building pipelines and data models that transform messy, siloed data into clean, accessible, and reliable datasets. You will play a key role in how we make informed decisions by providing the single source of truth that powers our dashboards, reports, and analytical tools.
You will contribute to building internal products and tools that make working with data easier, faster, and more reliable across Trendyol.
You will work on solutions such as SQL analysis services, automated data testing, and self-service reporting platforms. Using technologies such as Python, SQL, FastAPI, you will help automate repetitive processes, improve developer productivity, and enhance the overall analytics experience.
Responsibilities
- Partner with Product Managers and engineering teams to design, develop, and maintain scalable and reliable data models and metric layers for new and existing data product initiatives.
- Transform large, complex datasets from raw sources into clean, tested, and documented data assets that empower self-service analytics for end-users (analysts, data scientists, business teams).
- Own the end-to-end design, development, and maintenance of SQL-based data models, ensuring consistency, performance, and reliability within the data warehouse.
- Act as the product owner for our analytics platform, driving the standardization of data definitions and metadata to establish a "single source of truth." Additionally, lead the development of our next-generation platform that enables users to conduct self-service analysis through Large Language Models (LLMs) and AI Agents.
- Collaborate closely with business teams to understand their data exploration and analysis needs, influencing data roadmaps and prioritization based on their requirements.
- Deeply understand and empathize with Trendyol's customers and their journey with the product from a data perspective.
- Develop Python-based applications, APIs, and automation solutions to simplify repetitive tasks and support self-service analytics capabilities.
- Participate in the end-to-end development lifecycle, including requirement analysis, development, testing, deployment, troubleshooting, and continuous improvement.
- Identify opportunities to automate manual processes, improve existing tools, and enhance the user experience of internal products
Expected Qualifications
- Bachelor's degree or higher in a quantitative discipline such as Computer Science, Mathematics, Engineering, or a related field.
2+ years of professional experience in analytics engineering, data warehousing, or data modeling. Experience in an e-commerce environment is a strong plus. - Strong understanding of modern data warehousing concepts, including fact tables, dimensions, star schemas, and slowly changing dimensions.
- Expert-level proficiency in SQL and hands-on experience with the data modeling layer of modern BI and data visualization tools (e.g., Looker, Tableau).
- Proven hands-on experience in data modeling, data lake technologies, and large-scale data warehousing architecture.
- Experience applying software engineering best practices to data, including version control (Git) and CI/CD.
- Ability to translate complex data concepts and model designs for both technical and non-technical stakeholders, enabling them to tell stories with data.
- An agile mindset for data product development.
- Good programming skills in Python and a solid understanding of software development fundamentals, including object-oriented programming, clean code, and basic design principles.
- Basic understanding of REST APIs and backend service development concepts, preferably with hands-on experience in FastAPI or similar frameworks
- Familiarity with object-oriented programming language is a plus.
Skills Required
- Bachelor's degree or higher in Computer Science, Mathematics, Engineering, or a related quantitative discipline
- 2+ years of professional experience in analytics engineering, data warehousing, or data modeling
- Experience in an e-commerce environment
- Strong understanding of modern data warehousing concepts, including fact tables, dimensions, star schemas, and slowly changing dimensions
- Expert-level SQL proficiency
- Hands-on experience with the data modeling layer of BI and data visualization tools such as Looker or Tableau
- Hands-on experience in data modeling, data lake technologies, and large-scale data warehousing architecture
- Experience with version control using Git and CI/CD
- Ability to explain complex data concepts to technical and non-technical stakeholders
- Agile mindset for data product development
- Good programming skills in Python
- Understanding of object-oriented programming, clean code, and basic design principles
- Basic understanding of REST APIs and backend service development
- Hands-on experience with FastAPI or similar frameworks
- Familiarity with an object-oriented programming language
What We Do
We were founded in 2010 with a dynamic and agile start-up spirit. Since then, we have grown into a decacorn, backed by Alibaba, General Atlantic, Softbank, Princeville Capital, and several sovereign wealth funds. We believe that technology is the driver; e-commerce is the outcome. Thanks to our dedicated team, we are one of the top five e-commerce companies in EMEA and one of the fastest-growing e-commerce companies in the world! We deliver more than 1.5 million packages every day across 27 countries. We offer our 30 million customers a flawless shopping experience. Dreaming big is in our DNA: We're gearing up to be the leading global e-commerce platform. As a dynamic and passionate company, we are constantly growing with Trendyol Tech, one of the top R&D centres; Trendyol Express, the fastest growing delivery network; Dolap, the largest second-hand goods platform; and Trendyol Go, our instant food and grocery delivery service. And we’re not done yet! Now, we are on a journey to expand the positive impact we create to international markets. We opened our first international office in Berlin in May 2022 and Amsterdam followed in October 2022 and may others are on the way.
