Senior Data Developer

This is a fully remote position, open to applicants in Poland.

📋 Description

• Develop and sustain data solutions within Databricks utilizing PySpark and SQL.

• Comprehend, modify, and enhance existing notebooks and data workflows.

• Integrate data from various systems to create dependable datasets for reports, operational activities, and business stakeholders.

• Establish and manage Delta tables, views, and data models, including daily snapshots and reference or mapping datasets.

• Convert business requirements into data logic in collaboration with analysts, Product Owners, and global teams.

• Examine unexpected results, pinpoint data problems, and implement checks for missing, duplicated, or inconsistent data.

• Oversee and enhance scheduled Databricks jobs that support recurring business functions.

• Ensure code is clear and maintainable while enhancing performance that influences reliability or processing duration.

• Investigate new technologies, including automation and containerized applications.

• Document data workflows, business rules, and troubleshooting procedures.

⛳️ Requirements

• Minimum of 2 years of experience in Data Engineering, Analytics Engineering, or data analysis.

• Proficient in designing ETL/ELT processes and constructing data models or layers for analytical goals.

• Background in maintaining production data processes, encompassing monitoring, problem diagnosis, and data quality assurance.

• Familiarity with cloud solutions, particularly Microsoft Azure.

• Practical expertise in SQL, Python, PySpark, and Databricks.

• Understanding of Data Lake / Delta Lake architecture and data modeling principles.

• Hands-on experience with Git and Azure DevOps, including managing changes across Development, Testing, and Production environments.

• Capability to translate business needs into technical solutions.

• Proficient in English to facilitate effective communication in an international setting.

• Strong analytical and logical reasoning skills, attention to detail, proactive mindset, and ability to prioritize under time constraints.

• Nice to have: experience in complex operational settings.

• Nice to have: understanding of dimensional modeling, including star schema, fact and dimension tables, data grain, and normalization or denormalization techniques.

• Nice to have: knowledge of advanced Databricks and Delta Lake features.

• Nice to have: experience with Kafka, Structured Streaming, or Event Hubs.

• Nice to have: familiarity with monitoring and alerting tools.

• Nice to have: knowledge of data security, access control, metadata management, and data lineage.

• Nice to have: experience using Jira and Confluence.

• Nice to have: Microsoft Certified: Fabric Analytics Engineer DP-600 or Databricks Data Engineer / Analyst Associate certifications.

🏝️ Benefits

• B2B type of cooperation.

• Opportunity to collaborate in a diverse, international, and cross-functional environment with leading experts.

• Space to experiment with new technologies, including AI tools, and implement innovations in production.

• Genuine ownership and tangible impact on strategic decisions.