Data Engineer

Навыки

• AWS
• Azure
• Big Data
• CI/CD
• Data Lake
• Data Quality
• Databricks

О компании и продукте

• Products & Systems Engineering
• We are seeking a skilled Databricks Engineer / Developer to design, develop and optimize scalable data pipelines and analytics solutions using the Databricks platform

Задачи

• Design, develop, and support data replication and integration solutions using HVR
• Design, build, and maintain scalable data pipelines using Databricks (Spark, Delta Lake)
• Develop and optimize ETL/ELT processes for structured and unstructured data
• Work with large datasets to ensure data quality, integrity, and performance optimization
• Implement data models and transformations for analytics and reporting
• Collaborate with data scientists and analysts to enable advanced analytics and ML workloads
• Integrate data from multiple sources including databases, APIs, and streaming systems
• Optimize Spark jobs for performance tuning and cost efficiency
• Implement data governance, security, and access controls
• Monitor and troubleshoot data pipelines and production issues
• Support CI/CD pipelines and DevOps best practices for data engineering workflows
• Support data migration and modernization initiatives
• Ensure data quality, governance, security, and compliance standards
• Create operational documentation, runbooks, and support procedures
• Participate in production support, issue resolution, and performance tuning activities
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Требования

• Bachelor’s degree in computer science, Engineering, or related field
• Technical Skills
• Hands-on experience with data engineering or big data development
• Strong knowledge of
• SQL / Oracle / SQL Server
• Java / JavaScript (preferred)
• Web-based applications and APIs (REST/SOAP)
• Strong experience with
• Databricks Platform
• Apache Spark (PySpark/Scala)
• SQL & Python
• Experience with Delta Lake and data lake architecture
• Hands-on experience with cloud platforms (Azure, AWS, or GCP)
• Familiarity with data orchestration tools (Azure Data Factory, Airflow, etc.)
• Knowledge of data warehousing concepts (Star schema, Snowflake schema)
• Experience with version control (Git) and CI/CD pipelines
• Strong understanding of data pipeline optimization and performance tuning
• Tech Stack
• Databricks (Spark, Delta Lake)
• Python / PySpark / SQL
• Azure (ADLS, Synapse, ADF) / AWS (S3, Redshift, Glue)
• Git, CI/CD tools
• Data visualization tools (Power BI, Tableau)
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