Resumen del rol

Senior Data Engineer

Requisitos y responsabilidades

Contenido del rol extraído en secciones para revisar más rápido.

Key Responsibilities

  • Design and develop robust, scalable data pipelines using Azure Data Factory (ADF)
  • Build and optimize data processing workflows using Databricks and Apache Spark
  • Implement declarative pipeline solutions using Lakehouse architecture and best practices
  • Write and optimize complex SQL queries for data transformation and analysis
  • Develop PySpark applications for large-scale data processing
  • Collaborate with data scientists, analysts, and stakeholders to understand data requirements
  • Ensure data quality, security, and compliance across all pipelines
  • Monitor, troubleshoot, and optimize data pipeline performance
  • Document technical solutions and maintain best practices documentation
  • Mentor junior team members and contribute to team knowledge sharing

What we're Looking For

  • Proficient in building scalable data solutions using Azure and Databricks
  • Skilled in SQL and PySpark for data transformation and processing
  • Capable of implementing declarative, maintainable pipeline architectures
  • Detail-oriented with a focus on data quality and performance optimization
  • Collaborative and able to work effectively with cross-functional teams
  • Proactive in staying current with emerging data engineering technologies and best practices
  • Communicative and able to explain complex technical concepts clearly

Must-Have Technical Skills

  • Azure Data Factory (ADF)“ Proven experience designing and implementing data integration solutions
  • Databricks“ Hands-on experience with Databricks platform and workspace management
  • Apache Spark “ Strong expertise in distributed data processing using Spark framework
  • Lakeflow & Declarative Pipelines – Experience building declarative, maintainable data pipelines
  • SQL – Advanced proficiency in writing optimized SQL queries for complex data transformations
  • PySpark “ Strong programming skills in PySpark for data processing and ETL operations

Additional Desired Qualifications:

  • Experience with cloud platforms (Azure, AWS, or GCP)
  • Knowledge of data warehousing concepts and modern data architecture
  • Familiarity with version control systems (Git)
  • Understanding of CI/CD pipelines and DevOps practices
  • Experience with data quality frameworks and testing methodologies
  • Knowledge of big data technologies and distributed computing

Required Experience

  • 5+ years of professional experience in data engineering or related roles
  • 3+ years of hands-on experience with cloud-based data platforms
  • Proven track record of designing and implementing production-grade data pipelines
  • Strong problem-solving skills and attention to detail

Education

  • Bachelor's Degree in Computer Science, Engineering, Mathematics or related field OR
  • Related Field or Professional experience

Why Join Us?

  • Work with cutting-edge data engineering technologies
  • Collaborate with a talented and innovative team
  • Opportunity to build impactful data solutions at scale
  • Professional growth and continuous learning opportunities
  • Competitive compensation and benefits package
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FocoData EngineeringÁrea del rol
Señal de senioritySeniorNivel del candidato
StackAWS, Azure, CI/CDSkills principales
Ubicación1 país aceptadoElegibilidad

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