JOBILY AI SUMMARY
What you'll do
- Build scalable ETL/ELT pipelines ingesting and transforming data from core banking sources
- Design and implement data models supporting analytics, ML feature stores, and BI use cases
- Develop data quality frameworks including profiling, validation, anomaly detection, and automated remediation
- Perform exploratory data analysis and profiling to identify patterns and quality issues
- Create data validation tools and quality checks to ensure accuracy in pipelines
- Manage cloud data infrastructure on Azure using Databricks and ADLS Gen2
- Implement CI/CD for data pipelines with Azure DevOps and infrastructure-as-code
- Enforce data governance, compliance, and lineage aligned with banking regulations
Key requirements
- 2+ years' experience
- Python and PySpark programming with SQL and SparkSQL skills
- Expertise in Databricks and Azure Data Lake Storage (ADLS Gen2)
- Strong knowledge of ETL/ELT design patterns and data modelling techniques (dimensional, data vault, star)
- Experience with data quality frameworks and data governance compliance (GDPR, PSD2)
- Familiarity with Azure DevOps, Git, CI/CD pipelines, and dbt for data transformation and testing
- Experience with Apache Airflow for data orchestration and monitoring tools for pipeline observability
- Computer Science / Engineering / Information Systems / related field
Benefits
- Competitive salary and benefits including life/health insurance, bonuses, company car (depending on management), flexible work arrangements, employee share purchase plan, parental leave, training & development, career coaching, diverse culture, and relocation benefits under Brain Regain initiative.
About the job
ARE YOU READY to step into the New Era (NewRA) of AI-driven banking? At Accenture Newra AI Hub, we are not just building technology, we are redefining how banking operates. As part of our strategic collaboration with Piraeus, Newra is designed to responsibly embed AI at the core of its business…


