
Senior Data Engineering Manager
6 days ago
We are seeking experienced leaders to guide our data engineering teams in designing and delivering scalable data pipelines and analytics platforms on Microsoft Azure and Databricks.
Key responsibilities include:
- Leading, mentoring, and growing a team of data engineers working on large-scale distributed data systems.
- Architecting and overseeing the development of end-to-end data solutions using Azure Data Services and Databricks.
- Collaborating with cross-functional teams to understand requirements and deliver impactful data products.
- Driving best practices in data engineering, coding standards, version control, CI/CD, and monitoring.
- Ensuring high data quality, governance, and compliance with internal and external policies.
- Optimizing performance and cost efficiency of data infrastructure in the cloud.
The ideal candidate will have:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 8+ years of experience in software/data engineering with at least 3 years in a leadership or managerial role.
- Hands-on experience with Big Data ecosystems (Spark, Hive, Hadoop), Azure Cloud Services (Data Lake, Data Factory, Synapse Analytics, Blob Storage), and Databricks (including Delta Lake, MLFlow, Unity Catalog).
- Strong programming skills in Python, Scala, or Java.
- Deep understanding of data modeling, ETL/ELT processes, and performance tuning.
- Experience managing Agile teams and delivering complex projects on time.
- Excellent problem-solving, leadership, and communication skills.
This is an exciting opportunity for data engineering professionals looking to take their skills to the next level and make a meaningful impact on our organization.
We value innovation, teamwork, and continuous learning. If you are passionate about data engineering and want to be part of a dynamic team, we encourage you to apply.
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