Sr. Data Engineer (R14153)

Role overview Join a senior data engineering team building the platforms that power a mission-driven financial services organization. Design, develop, and scale data architectures and pipelines that turn vast volumes of structured and unstructured data into reliable insights for the business.

Responsibilities - Architect and implement scalable, efficient, and reliable data platforms supporting analytical and operational workloads. - Build and maintain data pipelines, ETL processes, and integration solutions across large structured and unstructured datasets. - Optimize data pipelines, warehouses, and lakes for performance, reliability, scalability, and security. - Partner with stakeholders to gather requirements, build domain expertise, and translate business needs into effective data models. - Establish data quality standards, validation rules, documentation, and governance practices. - Implement monitoring and observability to surface bottlenecks, improve performance, and strengthen platform reliability. - Provide technical leadership on architecture, scalability, monitoring, and extensibility decisions. - Lead code reviews, mentor junior engineers, and contribute to a culture of continuous learning. - Take ownership of production issues, including root-cause analysis and long-term resolution. - Drive cross-functional engineering initiatives from requirements through delivery, keeping stakeholders informed of progress and risks. - Identify practical ways to apply AI tools to boost engineering productivity, analysis, and documentation.

Requirements - 8+ years of data engineering experience with strong data architecture, ETL, and database management background. - Strong programming in Python or PySpark, plus experience with Java or Scala. - Proven track record building end-to-end data pipelines and integration solutions. - Deep SQL knowledge and experience with relational and NoSQL databases. - Hands-on experience with big data platforms such as Spark, Kafka, or Hadoop. - Experience with orchestration and scheduling tools such as Airflow, Databricks, or Jenkins. - Background designing and operating scalable, secure cloud-based data systems on AWS, Azure, or GCP. - Comfort working in Agile environments (Scrum, Lean, or Kanban). - Demonstrated mentoring and technical leadership within a team.

Nice to have - Bachelor's or Master's degree in Computer Science, Data Science, or a related field. - Databricks experience or certification. - Experience with AWS Redshift, S3, Azure SQL Data Warehouse, or comparable cloud data services. - Background implementing data governance, data quality, or observability frameworks. - Experience leading cross-functional or multi-month engineering initiatives. - Familiarity with AI-assisted engineering tools for development, troubleshooting, and documentation.

Benefits and work setup - Medical insurance, savings fund, life insurance, and internet and electricity allowance (eligible employees). - Paid time off including vacation and parental leave. - Remote-eligible role; specific benefits vary by country of employment.