Back
Metro location and broad Databricks/AWS requirements increase competition, though seniority moderates candidate pool.
Deep data architecture plus finance and SAP ERP experience limit cross-industry transferability.
Explicit 12+ years requirement plus mandated Databricks, AWS, and data architecture skills make filtering strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and optimize finance data architecture on Databricks platform from data ingestion to business consumption layers.
Develop, maintain, and document finance data products enabling scalable AI/ML and digital use cases across the organization.
Provide hands-on data architecture support, incident handling, and collaborate with various stakeholders to improve data quality and architecture roadmaps.
Master’s degree in engineering, computer science, management information systems, or related field.
12-15+ years of professional experience in data architecture, modeling, engineering, and enterprise software development.
Experience with finance domain data and enterprise systems such as SAP ERP FI/CO, FSCM.
Technical expertise in Databricks, AWS services (Glue, EMR, Athena), Spark, Apache Kafka, Airflow, DBT, Terraform, GitLab/GitHub, and coding in SQL and Python.
Strong expertise in finance data domain combined with extensive hands-on experience managing complex enterprise data landscapes.
Ability to translate strategic business goals into scalable data architecture decisions with proficiency in enterprise data product lifecycle management.
Experience working in global, agile, cross-cultural teams with strong collaboration and proactive ownership in DataOps and DevSecOps practices.