Databricks Data Engineer

Our client is a rapidly growing, automation-led service provider specializing in IT, business process outsourcing (BPO), and consulting services. With a strong focus on digital transformation, cloud solutions, and AI-driven automation, they help businesses optimize operations and enhance customer experiences. Backed by a global workforce of over 32,000 employees, our client fosters a culture of innovation, collaboration, and continuous learning, making it an exciting environment for professionals looking to advance their careers. Committed to excellence, our client serves 31 Fortune 500 companies across industries such as financial services, healthcare, and manufacturing. Their approach is driven by the Automate Everything, Cloudify Everything, and Transform Customer Experiences strategy, ensuring they stay ahead in an evolving digital landscape. As a company that values growth and professional development, our client offers global career opportunities, a dynamic work environment, and exposure to high-impact projects. With 54 offices worldwide and a presence in 39 delivery centers across 28 countries, employees benefit from an international network of expertise and innovation. Their commitment to a ‘customer success, first and always‘ philosophy ensures a rewarding and forward-thinking workplace for driven professionals. We are currently searching for a

Databricks Data Engineer: Responsibilities Design, develop, and maintain data pipelines

using Databricks and Apache Spark. Integrate data from various sources

into Databricks, ensuring quality and consistency. Optimize Spark jobs

for performance and cost efficiency. Collaborate with data scientists, analysts, and stakeholders to understand requirements and deliver solutions. Create and maintain data models

to support analytics and reporting. Monitor and troubleshoot

data pipelines. Document processes, architectures, and workflows. Apply best practices in data engineering and ensure compliance with governance policies. Requirements 6+ years of experience in Data Engineering , with strong focus on Databricks and Apache Spark. Proficiency in Python, Scala, or Java. Experience with cloud platforms

(AWS, Azure, or Google Cloud). Strong SQL skills

for querying and data manipulation. Familiarity with

data warehousing concepts and tools. Version control experience

(Git). Strong communication skills for cross-functional collaboration. Desired Experience with machine learning frameworks and libraries. Knowledge of data visualization tools. Familiarity with CI/CD practices for data pipelines. Languages Advanced Oral English. Native Spanish. Note: Fully remote.

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Keywords: Databricks, Apache Spark, Data Engineer, Data Pipeline, Big Data, Python, Scala, Java, SQL, AWS, Azure, GCP, Data Modeling, Data Warehousing 6+ years of experience in Data Engineering , with strong focus on Databricks and Apache Spark. Proficiency in Python, Scala, or Java. Experience with cloud platforms

(AWS, Azure, or Google Cloud). Strong SQL skills

for querying and data manipulation. Familiarity with

data warehousing concepts and tools. Version control experience

(Git). Strong communication skills for cross-functional collaboration.