Senior Data Engineer (Python & Oracle PLSQL) - Financial Services
Senior Data Developer
Required Education: Bachelor's degree in Business, Finance, Data Science or Analytics, Statistics, Engineering, or a similar field.
Required Qualifications/Skills/Experience: 8–10 years of relevant hands-on experience as a Senior Data Developer or Data Analytics Lead. Expert-level experience designing and maintaining Oracle PL/SQL queries. Expert-level Python programming skills. Strong understanding of relational databases. Experience performing in-depth data analysis and data profiling. Experience mentoring or leading other data analysts. Strong interpersonal, teamwork, consulting, and problem-solving skills. Excellent written and verbal communication skills. Experience identifying and implementing process improvements. Ability to effectively manage multiple small to large projects simultaneously in a cross-functional environment. Awareness and understanding of AI/ML tools and techniques in data analytics, including machine learning algorithms, natural language processing, and predictive modeling. Hands-on experience in data warehousing and data analytics development. Deep understanding of financial data and complex data scenarios. Ability to communicate technical solutions and findings clearly to technical and non-technical stakeholders.
Preferred Qualifications/Skills/Experience: Practical experience applying AI/ML techniques in data analysis projects. Exposure to data visualization tools such as Tableau and Power BI. Senior-level data development position responsible for liaising between business users and technologists and exchanging information in a concise, logical, and understandable manner in coordination with the Technology team. Combines technical, functional, analytical, and problem-solving skills to deliver high-quality insights and support business decisions. Requires hands-on experience with data warehousing, data analytics development, financial data, and complex data scenarios. Responsible for researching and evaluating emerging AI tools and techniques for potential application in data analysis projects. Works with business units such as Finance, Risk, and Operations to analyze complex financial data, identify trends, patterns, and anomalies, and provide actionable insights. Develops and optimizes SQL queries, Oracle stored procedures, triggers, and functions; uses Python and other analytical tools to support reporting, automation, data quality, reconciliation, and visualization. Acts as a subject matter expert for senior stakeholders and team members while contributing to complex, high-impact technology initiatives.
Job Duties: Analyze complex financial data and identify trends, patterns, and anomalies to provide actionable business insights. Write and optimize complex SQL queries for data extraction, reporting, and analysis. Develop Oracle stored procedures, triggers, and functions to automate data-related processes. Design and implement reporting solutions using SQL, Python, scripting, and other data analytical tools to deliver accurate and meaningful visualizations. Use Python and other programming languages to automate manual tasks and develop data reconciliation and data quality checks. Develop analytical reports and dashboards based on business requirements. Address and resolve complex data-related issues while ensuring data integrity and accuracy. Collaborate with team members, technology partners, and business partners to identify efficient and strategic solutions. Communicate technical solutions, application functions, findings, and financial data concepts to technical and non-technical stakeholders. Provide input during development and implementation phases, including formulation and definition of system scope, objectives, and necessary system enhancements for complex, high-impact projects. Own issue resolution, manage multiple program sub-streams, and assist in developing technology solutions based on analysis. Manage multiple responsibilities effectively while maintaining awareness of regulatory deadlines. Review existing processes critically to identify inefficiencies and automation opportunities. Author architectural proposals, technical solutions, and communication materials for senior management and key business partners. Guide stakeholders through complex data issues. Act as a subject matter expert to senior stakeholders and other team members. Mentor and lead other data analysts as needed. Serve as a change agent by identifying opportunities to improve processes and implement automation. Research and evaluate emerging AI tools and techniques for potential use in data analysis projects.
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