Direct message the job poster from Swiss Himmel
Talent Acquisition Specialist/Manager/Recruitment Consultant/ HR
Contract: 9–12 months (onsite, with possible extension)
We are looking for a Senior Data Engineer for our client with strong expertise in Azure Data Services, Databricks, and Python/PySpark to support large-scale data engineering and analytics initiatives within the Financial Services sector.
The role involves designing, building, and optimizing scalable data pipelines and solutions on Azure, collaborating with cross-functional teams to deliver high-quality, production-ready data systems.
Key Responsibilities
* Design, build, and maintain large-scale data pipelines using Azure Data Factory, Databricks, and Delta Lake.
* Develop and optimize ETL/ELT processes with a focus on performance and scalability.
* Write clean, efficient, and reusable code in Python and PySpark.
* Implement solutions leveraging Azure Data Lake, Azure SQL, and related services.
* Apply best practices for data storage, processing, and governance in cloud environments.
* Optimize Databricks clusters and workflows for cost and performance efficiency.
* Work closely with data architects, analysts, and business stakeholders to understand requirements and deliver solutions.
* Ensure data quality, reliability, and compliance across all deliverables.
* Identify opportunities to automate data workflows and improve processes.
Qualifications & Experience
* 5–8years of experience in Data Engineering roles.
* Hands-on experience with Python and PySpark for large-scale data processing.
* Solid understanding of ETL frameworks, data modeling, and data warehousing concepts.
* Experience working in the Financial Services domain (banking, capital markets, or asset management) is a plus.
* Strong problem-solving skills with the ability to work independently and in a team environment.
Skills Sets :
* Cloud-based data architecture (Azure Stack)
* Data governance & quality management
* Collaboration with business and technical teams
* Strong communication and analytical skills
* On-time and high-quality delivery of data pipelines
* Performance and cost optimization of cloud solutions
* Stakeholder satisfaction (business & technical teams)
* Continuous improvements in automation and data processes
* Contribution to innovation and best practices in cloud data engineering
Seniority level
* Seniority level
Mid-Senior level
Employment type
* Employment type
Contract
Job function
* Industries
IT Services and IT Consulting, Banking, and Insurance
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