Senior Data Engineer
Summary
Design and implement scalable data pipelines using Databricks, Airflow, and CI/CD to ensure reliable, high-quality data solutions for enterprise clients.
This is us
At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.
This is the job
Avenga is looking for a skilled Senior Data Engineer to join our team on a long-term engagement. As a Senior Data Engineer, you will bring strong hands-on Databricks expertise to help design robust architecture and engineering patterns, support data governance, and provide practical guidance across orchestration, DevOps, and data quality. You will work closely with cross-functional teams to structure workloads, define standards, and ensure our data solutions are reliable, scalable, and aligned with best practices.
This is you
Strong hands-on Databricks experience in real delivery environments
Practical experience with Airflow orchestration in combination with Databricks
Strong CI/CD experience for Databricks, including Git-based development, testing, deployment automation, operations
Experience with data quality / monitoring / DQ frameworks, ideally in Databricks or similar modern data platforms.
Ability to provide practical recommendations, alternatives, and consequences of choices
Ability to work in a supporting, collaborative mode
This is your role
Define Databricks architecture and engineering patterns, providing practical guidance on how to structure workloads, delivery patterns, standards, and reusable technical approaches in Databricks.
Support governance and the data management lifecycle, including metadata management, tagging, dictionaries, catalogs, and Unity Catalog setup and native options.
Help evaluate data quality / DQMS approaches, including native Databricks monitoring/profiling capabilities, process implications, and possible hybrid approaches.
Provide advice on orchestration options and trade-offs, including how Airflow can be used with Databricks jobs, along with best practices and standards.
Support the definition of practical DevOps approaches in terms of CI/CD, metadata/template-driven approach, monitoring and operations, and connection to dictionaries and catalogs (including tools).
Help define basic standards and conventions, such as naming conventions, repository structure, deployment principles, and selected governance guardrails.
At Avenga, everyone matters. We provide equal opportunities in recruitment, career development, and leadership, regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to fostering a work environment where our diverse community of employees, candidates, and business partners actively shapes our growth. By bringing together people from different backgrounds and experiences, we build a workplace where everyone feels free to be themselves while honoring the boundaries of others.