Data Engineer (Databricks) – Panama

at  Daugherty Business Solutions

Title: Data Engineer (Databricks) – Panama Overview:
¿Eres un ingeniero de software con mentalidad de consultor que quiere usar la tecnología para hacer del mundo un lugar mejor? Si ve potencial para la tecnología en todas partes y te encanta el desafío de dar vida a soluciones innovadoras, ¡queremos hablar contigo!
Daugherty Business Solutions is making a difference in the communities we work in around the world. With a strong growing economy driven primarily by it’s diverse and talented people, Daugherty is expanding our Panama Team! https://www.daugherty.com/panama-city/
Relocation is not available for this position. You must live in Panama today. Be a Panamanian citizen or authorized to work in Panama without sponsorship. At Daugherty we are committed to diversity, equity & inclusion, social impact, career growth & learning, and work-life balance. Work Remotely!
Daugherty Business Solutions brings a fresh approach to data engineering by delivering results through unmatched innovation and world-class technology and talent. This is why many of the most well-known companies in the world trust us with their mission-critical projects. As a team member at Daugherty, you will play an integral role in our company’s success and are recognized and valued for your contributions. We have an entrepreneurial culture with the maturity and security of a 35+ year company helping you to create your best work and take your career to the next level.
We are seeking a skilled and experienced Data Engineer with expertise in Databricks, Azure, and Spark to join our dynamic team. The ideal candidate will play a key role in designing, developing, and maintaining scalable data pipelines and analytics solutions to support our growing business needs. This position offers an exciting opportunity to work with cutting-edge technologies and collaborate with cross-functional teams to drive actionable insights from data.

Responsibilities:

• Design, develop, and deploy end-to-end data pipelines using Databricks, Azure Data Factory, and Spark to ingest, process, and analyze large volumes of structured and unstructured data.
• Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and translate them into technical solutions.
• Optimize and tune data pipelines for performance, reliability, and scalability to ensure efficient processing of data.
• Implement data governance and security best practices to ensure the integrity and confidentiality of data.
• Develop and maintain documentation, including data flow diagrams, technical specifications, and user guides.
• Stay up-to-date with emerging technologies and best practices in data engineering, cloud computing, and big data analytics.

Qualifications:

• Proven experience as a Data Engineer, with at least 5 years of hands-on experience in designing and building data pipelines.
• Proficiency in Databricks, Azure services (e.g., Azure Data Lake Storage, Azure Synapse Analytics), and Spark for big data processing and analytics.
• Strong programming skills in Python, Scala, or Java, with experience in writing complex SQL queries.
• Experience with data modeling, ETL/ELT processes, and data warehousing concepts.
• Excellent problem-solving skills and attention to detail, with the ability to troubleshoot and debug complex data engineering issues.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
• Able to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members.
• Ability to effectively communicate technical concepts to non-technical stakeholders.
• Relevant certifications in Databricks, Azure, or Spark (e.g., Azure Data Engineer, Databricks Certified Associate) are a plus.
• Bachelor’s degree in Computer Science, Engineering, or related field; Master’s degree preferred.

• Design, develop, and deploy end-to-end data pipelines using Databricks, Azure Data Factory, and Spark to ingest, process, and analyze large volumes of structured and unstructured data.
• Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and translate them into technical solutions.
• Optimize and tune data pipelines for performance, reliability, and scalability to ensure efficient processing of data.
• Implement data governance and security best practices to ensure the integrity and confidentiality of data.
• Develop and maintain documentation, including data flow diagrams, technical specifications, and user guides.
• Stay up-to-date with emerging technologies and best practices in data engineering, cloud computing, and big data analytics