Data Engineer @ Webinterpret Poland Sp. z o.o.
(práce v Polsku)

Data Engineer @ Webinterpret Poland Sp. z o.o.

Polsko

• 2+ years of experience designing and developing ETL pipelines in Python
• Comfortable writing and optimizing complex SQL queries in a data warehouse environment (e.g., Redshift).
• Hands-on experience building and maintaining dashboards and reports using BI platform (e.g., Tableau, Superset, Count).
• Capable of translating business needs into technical solutions, and comfortable verifying hypotheses with data.
• Hands-on experience with S3, Athena, and Redshift to manage large-scale data environments.
• Able to discuss technical concepts with both technical and non-technical audiences, including senior leadership, in English.

Webinterpret is all about taking e-commerce to the next level, empowering over 12,000 sellers to expand globally with ease. For more than 16 years, weve simplified cross-border selling with powerful tools that manage everything from AI-driven ad optimization and smart inventory syncing to handling currency fluctuations and localizing listings for different markets.

What do we do? Our tool automatically translates, localizes, and lists your products on international marketplaces like eBay and Amazon. We handle everything—from currency conversion to shipping options—so you can expand your reach, boost sales, and tap into new markets without the hassle. We take care of international shipping and returns, making global e-commerce as simple as selling locally.

What makes us unique? We’re not just helping sellers go global—we’re making it effortless. Our AI-driven tools, smart automation, and deep expertise turn complex challenges into simple, powerful solutions for global growth.

From massive scale listings to seamless inventory management, we handle the complexity so sellers can focus on success.

About the Role:

We are looking for a Data Engineer who can blend robust data engineering practices with strong analytical skills. In this role, you will architect and maintain data pipelines, optimize our AWS-based Data Lake and Data Warehouse, and collaborate with stakeholders to produce meaningful, self-serve analytics. As we move toward modern data governance and AI-driven automation, you’ll be a key player in building and scaling our data infrastructure for the next phase of growth.

Short job description:

• Location: Remote / Warsaw
• Experience: Middle
  
• Work framework: Scrum / Kanban
• Employment Type: B2B
• Location: Fully remote, hybrid, or office based on your preference
  Flexible working hours: Yes (with a start time between 8.00 AM - 10.00 AM CET/CEST)

What We Do:

• We process 500M+ records daily in AWS (S3, EMR, Glue, Athena, Apache Hudi/Delta Lake).
• We operate an AWS Redshift-based Data Warehouse.
• We build and orchestrate data pipelines in Python-based tools.
• We integrate and transform data from multiple sources (SQL/NoSQL DBs, APIs, queues, files) for internal reporting.
• Our next major milestone focuses on self-service data solutions, data lineage, and best practices for securing sensitive data.

,[Design, develop, and optimize ETL/ELT pipelines in Python to ensure timely, accurate, and reliable data delivery., Leverage AWS S3, EMR, Athena, Redshift, and related services to build and maintain our Data Lake and Warehouse., Work with business stakeholders to define data requirements and model datasets in a scalable, reusable way., Monitor pipeline performance, optimize SQL queries in Redshift, and implement best practices for data validation and testing (e.g., Great Expectations)., Connect to various data sources (Salesforce, RabbitMQ, Kafka, REST APIs, SQL databases) and handle synchronization/ingestion at scale., Leverage BI tools (e.g., Tableau, Superset, Count) to develop dashboards and reports that support data-driven decisions across the company., Write complex SQL queries, clean and analyze data, and verify business hypotheses for ongoing and ad-hoc requests., Support our transition toward self-service analytics and AI-driven automation, ensuring data is easily accessible and well-structured., Collaborate with other teams (e.g., Software Engineers, DevOps) to maintain high data quality, completeness, and reliable data processing pipelines., Use Git (or similar) for code and documentation to promote stable, scalable workflows and predictable collaboration.] Requirements: AWS, ETL, Python, SQL, Git, Tableau, GitHub, pytest Tools: Jira, Confluence, GitHub. Additionally: Sport subscription, Training budget, Private healthcare, Flat structure, Small teams, International projects, Free coffee, Bike parking, Free snacks, In-house trainings, In-house hack days, Modern office, Startup atmosphere, No dress code.

Kategorie

data

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