Databricks Data Engineer

About the role

Accenture is seeking a Databricks Data Engineer to design, build, secure, and maintain scalable data pipelines on cloud platforms. The role focuses on transforming heterogeneous data sources into reliable, well‑documented datasets that enable analytics and business reporting.

Key responsibilities

• Design, build, and maintain scalable data pipelines using Databricks and Python.
• Develop ingestion, transformation, and processing workflows from diverse data sources.
• Work with cloud data platforms, data lakes, middleware, and enterprise data ecosystems.
• Ensure pipelines are secure, reliable, performant, and scalable.
• Implement monitoring, alerting, incident analysis, and performance optimization.
• Support data quality processes, including validation, cleansing, and consistency checks.
• Contribute to data modeling and transformation activities for business and technical teams.
• Document technical designs, data flows, and development processes.
• Collaborate with business, analytics, architecture, and operations teams.
• Participate in Agile delivery practices and continuous improvement of data engineering standards.

Required profile

• Minimum 4 years of experience in data engineering or data manipulation projects.
• Hands‑on experience with Databricks and strong Python programming skills.
• Experience designing and building ETL/ELT pipelines.
• Good understanding of data lakes, cloud data platforms, and modern data architectures.
• Familiarity with Azure and/or AWS cloud environments.
• Knowledge of data transformation methodologies and data modeling concepts.

Required skills

• Databricks
• Python
• Azure Data Factory
• Azure cloud services
• AWS data services
• Power BI