Job Description: Role Summary
We are looking for an experienced senior Data Analyst with strong hands-on expertise in SQL, Python, PySpark and Alteryx. The ideal candidate should have experience working with large and complex datasets, performing data mapping, data preparation, data quality validation and data analysis across multiple sources. Exposure to Banking, Credit & Lending, Retail Credit or Traded Credit domains will be highly preferred.
- Strong hands-on experience in SQL, Spark SQL/HQL, Python and PySpark for data exploration, transformation, analysis and validation.
- Hands-on experience in Alteryx, including designing and building workflows from scratch for extraction, transformation, loading and automation.
- Experience in setting up Alteryx workflows, connecting to multiple data sources, identifying source systems and automating repetitive data tasks.
- Working knowledge of Big Data frameworks such as Hadoop, Hive and Spark.
- Ability to perform complex data transformations using PySpark and Alteryx across large datasets.
- Strong exposure to data mapping, including defining mappings required to join datasets across multiple sources.
- Experience in data cleansing, data preparation, schema analysis and data quality validation.
- Understanding of ER diagrams, data modelling concepts, logical-to-physical mapping and data processing flows.
- Experience supporting data asset design and build activities by identifying critical data elements and defining reusable data asset mappings.
- Ability to create and maintain documentation for data mappings, subsystem design, technical design, business requirements, Alteryx workflows, processes and methodologies.
- Experience in dashboarding, visualization or reporting to support business analysis and insight generation.
- Ability to identify automation and process improvement opportunities to improve efficiency and productivity.
- Exposure to Agile delivery frameworks and tools such as Jira and Confluence.
- Banking domain knowledge, preferably in Credit & Lending, Retail Credit or Traded Credit.
Qualifications: Graduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.
