SENIOR DATA ENGINEER @ MANPOWERGROUP
We are actively seeking a highly skilled Senior Data Engineer to build and scale modern data infrastructure for a fast-growing organization within the Financial Services and Data & Analytics industry. In this role, you will play a critical part in designing, developing, and optimizing data pipelines and architectures that support advanced analytics and critical business intelligence initiatives. You will be responsible for ensuring the scalability and performance of data systems while maintaining the highest standards of data quality and governance.
The ideal candidate will have extensive experience in building scalable ETL/ELT pipelines and maintaining robust data warehouses and data lakes. You will work with large-scale structured and unstructured datasets, collaborating closely with data scientists and analysts to provide the foundational data structures needed for complex modeling. The position offers a competitive package ranging from $140,000 to $200,000 annually, plus bonuses and full benefits, based in New York.
The ideal candidate will have extensive experience in building scalable ETL/ELT pipelines and maintaining robust data warehouses and data lakes. You will work with large-scale structured and unstructured datasets, collaborating closely with data scientists and analysts to provide the foundational data structures needed for complex modeling. The position offers a competitive package ranging from $140,000 to $200,000 annually, plus bonuses and full benefits, based in New York.
Key Requirements
5+ years of professional experience in data engineering roles.
Strong proficiency in programming languages, particularly Python.
Advanced knowledge of SQL for complex data manipulation and querying.
Hands-on experience with Apache Spark for large-scale data processing.
Extensive experience with cloud platforms such as AWS, Azure, or GCP.
Proven track record with data warehousing solutions and architecture.
Strong understanding of big data technologies and distributed systems.
Ability to design and build scalable ETL and ELT pipelines.
Proficiency in maintaining and optimizing data lakes for performance.
Excellent collaboration skills for working with data scientists and analysts.
Experience in ensuring data quality, integrity, and corporate governance.