Technology->Business Intelligence - Reporting->SAP BW

Key Responsibilities
Lead end-to-end delivery of data engineering solutions leveraging Databricks and PySpark for scalable processing and transformation.
Design, build, and optimize batch/near-real-time pipelines with robust focus on performance, cost efficiency, and reliability.
Collaborate with SAP BW stakeholders to understand source models, data semantics, and reporting needs; translate them into contemporary data platform designs.
Develop reusable frameworks, coding standards, and best practices for Spark-based development and notebook/job orchestration.
Ensure data quality through validations, reconciliation checks, and robust error handling/monitoring across pipelines.
Drive technical discussions, estimate work, plan sprints, and manage delivery risks/dependencies for the team.
Mentor engineers, conduct code reviews, and enforce secure, maintainable, and well-documented implementations.
Partner with platform/DevOps teams to support CI/CD, setting management, and production readiness for Databricks workloads.

Minimum

Qualifications:
Bachelor’s or Master’s degree (BTECH, MTECH, MCA, MSC) in Computer Science, Engineering, or a related field.




7–9 years of overall experience with strong hands-on expertise in Databricks and PySpark for large-scale data processing.
Strong experience working with SAP BW concepts and data structures to support analytics/reporting requirements.
Solid understanding of data modeling, ETL/ELT patterns, and performance tuning in distributed data processing environments.
Ability to lead technical delivery, collaborate with stakeholders, and communicate clearly across teams.

Preferred

Qualifications:
Experience modernizing or integrating SAP BW data with cloud-based lakehouse architectures using Databricks.
Solid knowledge of Spark optimization techniques (partitioning, caching, joins, file sizing) and production-grade pipeline design.
Exposure to Delta Lake patterns (ACID tables, MERGE, time travel) and building curated layers for analytics consumption.
Experience with workflow orchestration and operational monitoring for data pipelines, including alerting and SLA management.
Proven ability to guide teams through design reviews, code quality improvements, and delivery governance in agile environments.

📌 Sap Bw Hyderabad
🏢 Infosys
📍 Hyderabad