Data Engineer
1 week ago
Company Description
KData AI is a leading firm in Data and AI Engineering in the cloud, dedicated to delivering exceptional results for businesses worldwide. We specialize in transforming data into actionable insights through innovative AI and engineering solutions. Follow us on Twitter: @KDataAI.
Role Description
This is a full time role for a Data Engineer. The Data Engineer will be responsible for designing, building, and maintaining data pipelines, performing data modeling, and ensuring data quality. They will also be involved in developing and optimizing ETL processes, managing data warehousing solutions, and conducting data analytics. Collaboration with cross-functional teams to understand data requirements and provide support for data-driven decision making is also part of the daily tasks.
Job Description: We are looking for an experienced and driven Data Engineer with strong technical skills and industry knowledge in regulatory technology, banking, and financial services. As a Data Engineer, you will play a critical role in managing and transforming large datasets, creating data pipelines, and supporting advanced analytics initiatives. You will leverage your expertise in Databricks, AML, fraud detection, and capital markets to deliver high-impact solutions in the regulatory technology space.
Key Responsibilities:
- Develop and maintain data pipelines and ETL processes for AML, fraud detection, and regulatory compliance applications.
- Utilize Databricks to design and implement scalable data architectures, ensuring efficient processing and storage of large datasets.
- Collaborate with data scientists, analysts, and other engineers to support advanced analytics for fraud detection, transaction monitoring, and AML investigations.
- Design and implement data solutions that comply with banking regulations, capital markets data requirements, and industry best practices.
- Work with cross-functional teams to develop data-driven solutions to identify, monitor, and mitigate fraud and money laundering risks.
- Optimize and troubleshoot data processing systems to ensure high performance, accuracy, and reliability.
- Provide subject matter expertise on AML, fraud detection, banking, and capital markets data requirements.
Required Qualifications:
- Bachelor's degree in Computer Science, Engineering, or related field (Master's degree is a plus).
- Databricks Certification is required.
- 4+ years of experience as a Data Engineer or in a similar role.
- Proven experience working in the banking, capital markets, or financial services industry.
- Strong understanding of AML regulations, fraud detection systems, and transaction monitoring.
- Experience with data engineering tools and platforms such as Databricks, Spark, Python, SQL, and cloud services (AWS, Azure, or GCP).
- Familiarity with regulatory reporting standards and compliance frameworks in the financial industry.
- Solid knowledge of data warehousing, data pipelines, ETL processes, and data architecture.
- Experience with big data technologies, data lakes, and real-time data processing.
- Strong problem-solving and analytical skills with the ability to work in a fast-paced, dynamic environment.
Preferred Qualifications:
- Familiarity with regulatory technologies and tools in the financial industry.
- Experience in Capital Markets, Securities, and Trading data.
- Knowledge of machine learning algorithms for fraud detection.
- Experience with data governance and data privacy regulations.
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