Senior AI Data Software Engineer
New
E
EPAMData engineering
Opportunity to work remotely within PolandFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Exceptional oral and written communication skills in English (B2+)
- Experience
- 4+ years experience in software development with Data Software Engineering technologies
- Required Skills
- PythonSQLETLGCPAmazon Web ServicesAzureSparkDatabricks
Requirements
- Have 4+ years of software development experience with data software engineering technologies.
- Have advanced knowledge of Python.
- Be proficient with Spark and Databricks.
- Have experience with cloud platforms such as Azure, Amazon Web Services, or Google Cloud Platform.
- Have experience using AI development tools such as Claude Code, GitHub Copilot, or Cursor.
- Understand data file formats including JSON, Parquet, and Avro.
- Have hands-on experience with SQL and NoSQL databases, including Cassandra and MongoDB.
- Be proficient in data warehousing solutions and ETL processes.
- Hold a bachelor’s degree in Computer Science, Mathematics, or a related technical field.
- Have strong analytical and problem-solving skills and attention to detail.
- Know software development methodologies and best practices.
- Have exceptional oral and written communication skills in English at B2+ level.
Responsibilities
- Implement data ingestion from sources including RDBMS, REST HTTP APIs, flat files, streams, time-series data, and SAP.
- Research and use data software engineering technologies for data ingestion.
- Process and transform data using Spark, Databricks, and cloud services.
- Implement agentic development environments as part of AI adoption.
- Execute project-specific business logic using languages supported by the primary data platform.
- Optimize data retrieval, develop dashboards, and perform data validation.
- Collaborate with data scientists, analysts, and IT professionals.
- Provide guidance on data software engineering practices and technology trends.
- Maintain the integrity and security of data sources and platforms.
- Troubleshoot, debug, and upgrade data systems and applications.
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