Data Engineer
Core
Designing, developing, and maintaining ETL/ELT data pipelines and data lakehouse solutions for financial services and investment banking clients.
Role type
Senior Data Engineer (Cloud & Data Platform)
Builds
Scalable data pipelines, data lakehouse architectures, and regulatory reporting solutions for financial institutions.
Domain
Financial Services / Investment Banking / Cloud Data Engineering
Required skills
Python, SQL, PySpark, Databricks, Azure (ADLS, Data Factory, Synapse), REST APIs, Git, CI/CD, Data Modeling (Dimensional/Medallion), Data Quality, Performance Tuning
Preferred skills
Kafka, Azure Event Hub, Power BI, Tableau, Data Vault, Banking domain knowledge (risk management, regulatory reporting)
Technologies
Databricks, Azure, PySpark, Kafka, Event Hub, Power BI, Tableau, Git, Azure DevOps
Responsibilities
Design and optimize ETL/ELT pipelines for structured and semi-structured data; Build and maintain data lakehouse solutions supporting analytics and regulatory processes; Integrate data from diverse sources including databases, APIs, and event streaming systems; Collaborate with Business Analysts and Architects to ensure safe and efficient data solutions; Analyze incidents and support production environments; Optimize data solution performance and scalability.
Seniority
Mid-Senior (3-7+ years experience)
