Sap Architect

About the Role

We are looking for a hands-on DatabricksTableau–SAP Architect who can single-handedly design, build, and scale our analytics and BI capability from the ground up. This is not a purely strategic or advisory position you will be writing pipelines, building dashboards, and solving integration problems yourself in the early stages, while simultaneously identifying, hiring, and mentoring a high-performing team as the function matures.

The ideal candidate is a rare combination of a data engineering architect (Databricks), a visualization expert (Tableau), and someone who deeply understands SAP systems and data structures, and can bridge all three into a cohesive, enterprise-grade analytics platform.

Key Responsibilities

Architecture & Hands-On Delivery

• Design and build end-to-end data pipelines on Databricks (Lakehouse architecture, Delta Lake, PySpark/SQL) to ingest, transform, and model data from SAP and other enterprise sources.
• Architect scalable, secure, and cost-optimized data platforms (batch and streaming) covering ingestion, transformation, governance, and consumption layers.
• Personally build, optimize, and maintain complex Tableau dashboards and data visualizations for business stakeholders not just review others' work.
• Define and enforce data modeling standards (star/snowflake schemas, semantic layers) to ensure dashboards are fast, accurate, and reusable.
• Own performance tuning across Databricks jobs, SQL warehouses, and Tableau extracts/live connections.

SAP Expertise

• Understand SAP data structures (SAP ECC modules such as FI/CO, MM, SD, etc.) and extract/transform SAP data (via SLT, CDC, BW, OData, or direct extractors) into Databricks.
• Partner with SAP functional/technical teams to define extraction logic, resolve data discrepancies, and ensure data integrity from source to dashboard.
• Advise on integration patterns between SAP and the Databricks/Tableau ecosystem (real-time vs. batch, replication tools, etc.).

Team Building & Leadership

• Build the analytics engineering/BI team from scratch define role requirements, interview, hire, and onboard talent.
• Set up team structure, ways of working, coding/design standards, and review processes.
• Manage performance actively set clear KPIs, provide regular feedback, and make retention/promotion/exit decisions based on demonstrated performance rather than tenure.
• Mentor junior/mid-level engineers and analysts on Databricks and Tableau best practices.
• Act as the technical escalation point until the team is mature enough to self-manage.

Stakeholder & Governance

• Work directly with business stakeholders to gather requirements and translate them into technical designs and dashboards.
• Establish data governance, access control, and documentation practices across the platform.
• Present architecture decisions and roadmap to leadership.

Required Skills & Experience

• 10+ years in data engineering/BI, with at least 3–5 years in an architect-level, hands-on role.
• Strong expertise in Databricks: Delta Lake, Spark (PySpark/Scala/SQL), Unity Catalog, workflows/jobs, cluster/cost optimization.
• Strong expertise in Tableau: dashboard design, calculated fields/LOD expressions, performance optimization, Tableau Server/Cloud administration.
• Solid working knowledge of SAP systems — data structures, key modules (FI/CO, MM, SD or relevant to business), and extraction methods (SLT, BW, CDS views, OData, third-party CDC tools like Qlik Replicate/Fivetran/SAP Datasphere).
• Proficiency in SQL and at least one scripting language (Python preferred).
• Experience designing data models (dimensional modeling, semantic layers) for BI consumption.
• Prior experience building a team from the ground up, including hiring and performance management.
• Strong stakeholder management and communication skills — able to work with both technical and business teams.

Preferred / Good to Have

• Experience with cloud platforms (Azure/AWS/GCP) hosting Databricks.
• Familiarity with SAP BW/4HANA or SAP Datasphere/Analytics Cloud.
• Exposure to CI/CD for data pipelines (DevOps for data/DataOps practices).
• Certifications: Databricks Certified Data Engineer/Architect, Tableau Desktop Specialist/Certified Professional, SAP certifications (any module).
• Experience in [insert relevant industry, e.g., manufacturing, retail, BFSI] domain.