Company Overview
Risk Resources LLP is a specialized consulting firm focused on providing advanced risk management, financial advisory, and data-driven analytical solutions. Operating at the intersection of finance and technology, the firm empowers global enterprises to navigate complex regulatory landscapes and optimize operational efficiency. With a culture rooted in intellectual rigor and precision, Risk Resources LLP maintains a high-performance environment where data-centric strategies drive critical decision-making for institutional clients.
Role Overview
As a Data Engineer, you will serve as a technical cornerstone in building and maintaining robust data pipelines that power our analytical frameworks. You will work closely with data scientists, financial analysts, and infrastructure teams to transform raw, disparate data into high-quality, actionable insights. Your contributions will directly influence the accuracy of our risk models and the speed at which our clients can respond to market shifts, ensuring that our data architecture remains scalable, secure, and highly performant.
Key Responsibilities
- Design and implement scalable ETL pipelines to ingest and process large-scale datasets, ensuring data integrity for downstream financial reporting.
- Develop high-performance data processing applications using PySpark to handle complex transformations and large-scale data aggregation tasks.
- Manage and optimize cloud-based data workflows using AWS Glue to ensure seamless integration across our distributed data environment.
- Maintain and migrate legacy data processing logic using Abinitio to ensure continuity and performance in our core data systems.
- Collaborate with cross-functional stakeholders to define data requirements and translate business objectives into efficient technical architectures.
- Monitor and troubleshoot data pipeline performance to minimize latency and ensure high availability for internal and client-facing dashboards.
Required Skillset
- Demonstrated expertise in building end-to-end data engineering solutions with 5 - 10 years of professional experience in data-heavy environments.
- Advanced proficiency in PySpark and AWS Glue for developing distributed data processing applications within cloud ecosystems.
- Strong technical command of Abinitio for complex data integration and legacy system management.
- Ability to write clean, maintainable code and optimize SQL queries for large-scale relational and non-relational databases.
- Strong communication skills with the ability to articulate complex technical concepts to non-technical stakeholders and business leaders.
- Proven capability to work effectively in a hybrid office environment in Bangalore, demonstrating self-management and collaborative problem-solving.
- A Bachelors or Masters degree in Computer Science, Engineering, or a related quantitative field is preferred.
(ref:hirist.tech)
