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Responsibilities
Job Responsibilities:
• Design, develop, and maintain scalable data pipelines using PySpark, Hive and Hadoop.
• Build and manage data lakes and warehouses on AWS, Asure or GCP.
• Work extensively with Databricks – including Delta Lake, DLT pipelines, and workspace management.
• Automate deployment processes using DevOps tools such as Terraform, Git, and Jenkins is good to have.
• Collaborate with cross-functional teams to define data requirements and integrate data pipelines with analytics and ML platforms.
• Optimize SQL queries, ETL processes, and data models for performance and scalability.
• Participate in Agile/Scrum ceremonies and contribute to continuous improvement of engineering practices.
Job requirements:
• 3+ years of professional experience in data engineering or related roles.
• Strong proficiency in Python and SQL ; hands-on experience with PySpark is mandatory.
• 3+ years of experience working with Apache Spark and Hadoop ecosystems .
• 2+ years of hands-on experience with Databricks , including DLT, Delta Lake , and workspace administration.
• Experience with DevOps practices and tools: Terraform, Git, Jenkins .
• Familiarity with data warehousing concepts.
• Experience working in Agile/Scrum environments .
• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication and ability to work collaboratively in a remote-first team.
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