Job Purpose
Responsibilities
Depending on the specific team and role, the Property Data Engineer may be responsible for some or all the following tasks:
- Develop and maintain data conversion programs using C#, Python, JavaScript, and SQL.
- Implement ETL workflows using tools such as Pentaho Kettle, SSIS, and internal applications.
- Collaborate with Analysts and Senior Analysts to interpret conversion instructions and translate them into executable code.
- Troubleshoot and resolve issues identified during quality control reviews.
- Recommend and implement automation strategies to improve data processing efficiency.
- Perform quality checks on converted data and ensure alignment with business rules and standards.
- Contribute to the development of internal tools and utilities to support data transformation tasks.
- Maintain documentation for code, workflows, and processes to support team knowledge sharing.
Programming (Skill Level: Advanced to Expert)
- Create and maintain conversion programs in SQL, Visual Studio using C#, Python or JavaScript.
- Use JavaScript within Pentaho Kettle workflows and SSIS for data transformation.
- Build and enhance in-house tools to support custom data processing needs.
- Ensure code is modular, maintainable, and aligned with internal development standards.
- Ensure code quality through peer reviews, testing and adherence to development standards.
)
- Execute and troubleshoot ETL processes using tools like Kettle, SSIS, and proprietary tools.
- Input parameters, execute jobs, and perform quality checks on output files.
- Troubleshoot ETL failures and optimize performance.
- Recommend and implement automation strategies to improve data processing efficiency and accuracy.
Data File Manipulation (Skill Level: Advanced to Expert)
- Work with a wide variety of file formats (CSV, Excel, TXT, XML, etc.) to prepare data for conversion.
- Apply advanced techniques to clean, merge, and structure data.
- Develop scripts and tools to automate repetitive data preparation tasks.
- Ensure data is optimized for downstream ETL and analytical workflows.
Data Analysis (Skill Level: Supportive Applied)
- Leverage prior experience in data analysis to independently review and interpret source data when developing or refining conversion programs.
- Analyze data structures, field patterns, and anomalies to improve the accuracy and efficiency of conversion logic.
- Use SQL queries, Excel tools, and internal utilities to validate assumptions and enhance the clarity of analyst-provided instructions.
- Collaborate with Analysts and Senior Analysts to clarify ambiguous requirements and suggest improvements based on technical feasibility and data behavior.
- Conduct targeted research using public data sources (e.g., assessor websites) to resolve data inconsistencies or fill in missing context during development.
Quality Control (Skill Level: Engineer-Level)
- Perform initial quality control on converted data outputs before formal review by Associates, Analysts, or Senior Analysts for formal review.
- Validate that the program output aligns with conversion instructions and meets formatting and structural expectations.
- Use standard scripts, ad-hoc SQL queries, and internal tools to identify and correct discrepancies in the data.
- Address issues identified during downstream QC reviews by updating conversion logic or collaborating with analysts to refine requirements.
- Ensure that all deliverables meet internal quality standards prior to release or further review.
Knowledge and Experience
- Minimum Education:Bachelors degree in Computer Science, Information Systems, Software Engineering, Data Engineering, or a related technical field; or equivalent practical experience in software development or data engineering.
- Preferred Education: Bachelors degree (as above) plus additional coursework or certifications in:
- Data Engineering
- ETL Development
- Cloud Data Platforms (e.g., AWS, Azure, GCP)
- SQL and Database Management
- Programming (C#, Python, JavaScript)
- 4+ years of experience in software development, data engineering, or ETL pipeline development.
- Expert-level proficiency in programming languages such as SQL, Visual Studio using C#, Python, and JavaScript.
- Experience with ETL tools such as Pentaho Kettle, SSIS, or similar platforms.
- Strong understanding of data structures, file formats (CSV, Excel, TXT, XML), and data transformation techniques.
- Familiarity with relational databases and SQL for data querying and validation.
- Ability to read and interpret technical documentation and conversion instructions.
- Strong problem-solving skills and attention to detail.
- Ability to work independently and collaboratively in a fast-paced environment.
- Familiarity with property assessment, GIS, tax or public property records data.
Preferred Skills
- Experience developing and maintaining data conversion programs in Visual Studio.
- Experience with property assessment, GIS, tax or public records data.
- Experience building internal tools or utilities to support data transformation workflows.
- Knowledge of version control systems (e.g., Git, Jira) and agile development practices.
- Exposure to cloud-based data platforms or services (e.g., Azure Data Factory, AWS Glue).
- Ability to troubleshoot and optimize ETL performance and data quality.
- Strong written and verbal communication skills for cross-functional collaboration.
