Databricks Data Engineer
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Role Summary
We are looking for a Databricks Data Engineer with strong Python skills to design, build, secure, and maintain scalable data pipelines across cloud data platforms. The role will focus on developing robust data flows from heterogeneous sources into usable, reliable, and well-documented datasets that support analytics, reporting, and business use cases.
The ideal candidate has hands-on experience with Databricks, Python, cloud data platforms such as Azure or AWS, and modern data engineering practices including data quality, monitoring, performance optimization, and operational support.
Key Responsibilities:
- Design, build, and maintain scalable data pipelines using Databricks and Python.
- Develop data ingestion, transformation, and processing workflows from heterogeneous data sources.
- Work with cloud data platforms, data lakes, middleware, and enterprise data ecosystems.
- Ensure data pipelines are secure, reliable, performant, and scalable.
- Implement monitoring, alerting, incident analysis, and optimization of data flows.
- Support data quality processes, including validation, cleansing, completeness checks, and consistency controls.
- Contribute to data modeling and transformation activities to make data usable for business and technical teams.
- Recommend and implement appropriate technical solutions for data consumption, data modeling, and interoperability needs.
- Maintain technical documentation, data flow diagrams, and development documentation.
- Collaborate with business, analytics, architecture, and operations teams to deliver high-quality data solutions.
- Participate in Agile delivery practices and contribute to continuous improvement of data engineering standards.
Preferred Skills
- Experience with Azure Data Factory, Azure cloud services, AWS data services, or similar cloud integration tools.
- Knowledge of DataOps practices.
- Experience with FinOps dashboards, cost optimization reporting, or data products supporting cloud cost management.
- Experience with Power BI or other reporting/dashboarding tools.
- Exposure to spec-driven development or AI-assisted development practices.
- Familiarity with enterprise security, governance, and operational standards.
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Experience/Required Skills:
- Strong hands-on experience with Databricks.
- Strong programming experience in Python.
- Minimum 4 years of experience in data engineering or data manipulation projects.
- Experience designing and building ETL / ELT data pipelines.
- Good understanding of data lakes, cloud data platforms, and modern data architectures.
- Experience with Azure and/or AWS cloud environments.
- Knowledge of data transformation methodologies and data modeling concepts.
- Ability to write clean, maintainable, and well-documented code.
- Good understanding of development methodologies and Agile delivery.
- Experience with data quality, pipeline monitoring, performance optimization, and operational support.
- Good communication skills in English; French is a plus depending on project context.
Benefits:
- Competitive salary and benefits package.
- Opportunities for continuous learning and professional growth.
- A collaborative and inclusive work environment.
- Exposure to cutting-edge technologies and innovative projects.
- Supportive leadership and career development programs.
Accenture does not discriminate on the basis of race, religion, color, sex, age, non-disqualifying physical or mental disability, national origin, sexual orientation, gender identity or expression, or any other basis covered by local law.
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