Data Engineer (Financial Services)

About the job Data Engineer (Financial Services)

About This Role

We are seeking a Junior to Mid-level Data Engineer to enhance our data capabilities by developing innovative solutions for data management and analytics. As a forward-thinking organization, we need someone who not only possesses technical expertise but also aligns with our vision and is eager to shape our data strategy.

Key Responsibilities

• Design and Development: Lead the design, development, and management of advanced data platforms, focusing on applications in the financial sector.
• Technical Excellence: Ensure the highest standards of technical excellence and reliability in data solutions.
• Data Integration: Play a crucial role in integrating financial market data to enable advanced analytics.

Requirements & Qualifications

• Education: Bachelor's degree or higher in Computer Science or a related field, or equivalent professional experience.
• Cloud Experience: Deep understanding of public cloud environments (AWS, GCP, Azure) and their application in data engineering.
• Experience: Minimum of 4 years in data engineering, with at least 3 years focused on financial services.
• Project Leadership: Proven experience in leading data engineering projects with team management responsibilities.
• Data Pipelines: Expertise in building and optimizing data pipelines for financial data analytics.
• Technical Skills: Proficient in data pipeline tools like Apache Flink or Apache Spark, and workflow management with Airflow. Advanced skills in SQL and experience with relational and non-relational databases.
• BI Tools: Familiarity with integrating BI tools (e.g., Tableau, Mode, Looker) and using REST and streaming protocols, particularly Kafka.
• Programming: Strong skills in a JVM language (Java, Kotlin, Scala).
• Data Management: Experience managing data quality, privacy, and sovereignty in compliance with financial industry standards.
• Agile Methodologies: Solid understanding of agile methodologies, CI/CD, testing, and monitoring in a production environment.
• Personal Qualities: Self-motivated, with a keen sense of ownership and a results-driven mindset. Comfortable with complex datasets and enthusiastic about learning and growth.
• Communication Skills: Excellent communication skills and a customer-centric approach to product development.

Nice-to-Haves

• Prior experience in a trading environment.
• Knowledge of CQRS/Event Sourcing patterns.
• Proficiency in AWS or GCP, Cassandra, Kafka, Kubernetes, Terraform.