Job Overview:
The ETL Developer is responsible for designing, developing, and maintaining Extract, Transform, and Load (ETL) processes to support data integration and reporting needs within an organization. This role involves working with various data sources, transforming data into actionable insights, and ensuring data quality and consistency across systems.
Key Responsibilities:
- ETL Design and Development:
- Design, develop, and implement ETL processes to extract data from multiple sources, transform it according to business requirements, and load it into data warehouses or databases.
- Create and optimize ETL workflows, scripts, and procedures to ensure efficient data processing.
- Data Integration:
- Integrate data from diverse sources such as databases, flat files, APIs, and cloud platforms.
- Ensure data accuracy and consistency by implementing data validation and cleansing processes.
- Data Transformation:
- Develop data transformation logic to convert raw data into meaningful and actionable information.
- Utilize tools and scripting languages to automate data transformation tasks and improve processing efficiency.
- Data Quality and Governance:
- Monitor and ensure the quality and integrity of data through regular audits and validation checks.
- Implement data governance practices and enforce data standards to maintain high-quality data.
- Performance Optimization:
- Analyze and optimize ETL processes for performance and scalability.
- Troubleshoot and resolve ETL-related issues and performance bottlenecks.
- Documentation and Reporting:
- Document ETL processes, data flows, and system configurations for reference and compliance purposes.
- Provide regular updates and reports on ETL processes, data integration, and performance metrics to stakeholders.
- Collaboration and Support:
- Collaborate with data analysts, data scientists, and other stakeholders to understand data requirements and deliver solutions.
- Provide support for data-related issues and assist in troubleshooting and resolving data-related problems.
- Continuous Improvement:
- Stay current with the latest ETL technologies, tools, and best practices.
- Recommend and implement improvements to enhance ETL processes and data management practices.
Mandatory skills: ETL, Python, Shell Scripting, Linux, FHIR, EDI, InterOp, Health care domain
Programming Languages: Excellent knowledge of Shell scripting and Python programming languages for data manipulation and transformation
Responsibilities: –
- 7-9 yrs of experience in designing ETL processes, pipelines, and SQL queries, and ensure data flow
- ETL: Proficiency in ETL processes and tools, with the ability to oversee and execute complex data transformations
- Data Migration: Extensive experience in data migration projects, demonstrating a track record of successful data transitions.
- Data Analysis: Ability to analyze data sources, understand data relationships, and develop strategies to extract, transform, and load data effectively.
- Databases: A strong understanding of relational databases (such as MySQL, Oracle, and SQL Server) and knowledge of SQL is essential.
- Data Management: Deep understanding of data management principles, including data mapping, data quality assurance, and data governance.
- Data Modeling: Understanding data modeling principles and practices to design efficient data structures and optimize data warehouse performance.
- Performance Tuning: Skills in optimizing ETL processes and database queries to improve performance and reduce load times.