DescriptionWe have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Lead Software Engineer at JPMorgan Chase within the Enterprise Technology, Global Technology Strategy team, you will be a key member of an agile team, responsible for designing and delivering secure, stable, and scalable market-leading technology products. Your role will involve implementing critical technology solutions across a variety of technical areas and business functions, all in support of the firm's business objectives.
We are seeking a talented Data Reporting and Analytics Specialist to collect, analyze, and present data to drive informed business decisions. The ideal candidate will have a strong background in data analysis, reporting, and visualization, with a passion for turning complex data into actionable insights. The successful candidate will work closely with cross-functional teams to identify key performance indicators (KPIs), develop reports and dashboards, and provide data-driven recommendations to improve operational efficiency and strategic decision-making.
Job Responsibilities:
- Collect, organize, and analyze large datasets to identify trends, patterns, and insights.
- Develop and maintain reporting frameworks, dashboards, and visualization tools to effectively communicate complex data to stakeholders.
- Collaborate with internal teams to identify key performance metrics and data requirements for reporting purposes.
- Conduct data mining and ad-hoc analyses to uncover business opportunities and areas for improvement.
- Monitor data quality and ensure data integrity by implementing data validation processes.
- Stay up-to-date with industry best practices and emerging trends in data analysis and reporting techniques.
- Present findings and recommendations to both technical and non-technical stakeholders in a clear and concise manner.
- Work closely with the IT team to optimize data storage, retrieval, and accessibility.
- Assist in the development and implementation of data governance policies and procedures.
- Contribute to software engineering communities of practice and events that explore new and emerging technologies
- Add to team culture of diversity, equity, inclusion, and respect
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Bachelor's degree in Mathematics, Statistics, Computer Science, or a related field.
- Proven experience working in data analysis, reporting, or a related field.
- Proficiency in data visualization tools (e.g., Tableau, Power BI, QlikView) and advanced knowledge of SQL.
- Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information.
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages.
- Overall knowledge of the Software Development Life Cycle
- Proficiency in programming languages such as Python, R, or SAS.
- Experience with statistical analysis and modeling techniques.
- Knowledge of data management principles, including data governance and data quality.
Preferred qualifications, capabilities, and skills
- Solid understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Familiarity with modern front-end technologies
- Familiarity with cloud-based data platforms (e.g., AWS, Azure Cloud) is a plus.
- A Master's degree is a plus.
- Experience with Snowflake is a plus.
- Strong attention to detail and the ability to work independently and manage multiple projects simultaneously and excellent communication skills, both written and verbal, with the ability to present complex data findings to non-technical stakeholders.
