Role Purpose:
- Implement ETL systems that are operationally stable, efficient and automated. This include technical solutions that are scalable, aligned with the enterprise architecture and can adapt to changes in business.
- Monitor and optimize batch jobs, including automation and scheduling. Consistently review and enhance performance with key focus on ease of maintenance & jobs reusability.
- Work closely with internal/external teams devise requirements of data integrations, specific to Data Warehouse/Data Marts implementations.
Key Accountabilities and Responsibilities
- Review business and technical requirements and ensure the data integration platform meets requirements.
- Apply industry best practices for ETL design and development.
- Produce written deliverables for technical design, system testing and implementation activities.
- Conduct System Testing - execute job flows, investigate system defects, resolve defects and document results.
- Work with DBAs, application specialists and technical services to tune performance of the system to meet performance standards and SLAs.
- Work with DBAs, application specialists and technical services to tune performance of the ETL system to meet performance standards and SLAs.
- Assist in the development, documentation and application of best practices and procedures
Skills & Competencies
- Familiarity with ETL tools like:
- PySpark, Python, Advanced SQL, Cloudera Data Platform (CDP) / Nifi, Unix/Linux scripting
- Azure Cloud Services, Databricks Data Platform, Azure Data Factory
- Azure Data Lake Store (ADLS)
- Fundamental AI knowledge
- Data Lineage, Data Quality, Data Classification, Metadata Management
- Medallion Architecture (Mid to Advanced Level)
- Data Pipeline Job/Workflow Orchestrator (for example Zena, Airflow, etc.)
- Understanding of data integration best practices, leading industry applications and features such as master data management, entity resolution, data quality assessment, metadata management, etc.
- Exposure in data warehouse architecture, data analysis/data profiling of source systems
- Able to function well in a fast-paced and adaptive environment.
- Financial domain experience is a plus
- Ability to work independently and communicate across multiple levels (Product owners, Executive sponsors, Team members)
- Work experience in Agile methodology is a plus
- A very good team player & good communication skills.
- Good interpersonal skills and the ability to collaborate with other technical teams, project management, client management and business analysts.
