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Tier-1 brand and metro location increase competition, Databricks/SAP specialization moderates density.
Core Databricks/Spark skills are transferable, but SAP/finance/regulatory experience raises domain specificity.
Explicit 7+ years and required Databricks, SAP and cloud expertise make filters stringent.
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Design, implement, and operate scalable cloud-based data pipelines and ETL/ELT processes on Databricks for global finance data.
Act as a functional lead and technical expert establishing data & analytics capabilities in the Finance GBS team in Bangalore, collaborating closely with HQ in Denmark.
Drive continuous improvement, best practices for data quality, observability, and support deployment, CI/CD, and incident resolution for finance data solutions.
Master’s degree in computer science, engineering, software development or related field.
At least 7 years of experience in data engineering roles.
Strong hands-on experience with Databricks (Spark, Delta Lake, notebooks, jobs), Python, SQL, and familiarity with data engineering frameworks.
Experience with cloud platform services (Azure/AWS/GCP), data modelling, orchestration tools, SAP ecosystem (e.g., S4, BDC or BW/BW4 HANA), and DevOps practices.
Experienced in designing end-to-end data pipeline architecture in regulated, finance-related environments with complex technical requirements.
Capable of bridging technical expertise and functional finance business understanding to deliver high-quality, valuable data solutions.
Proven ability to lead, coach, and collaborate across global teams, establishing robust data & analytics capabilities in a GBS setting.