Senior Data Engineer

3 days ago

San Antonio, TX, United States RICEFW Technologies Full time
Senior Data Engineer - Lakehouse & Power BI Analytics

Onsite - San Antonio, TX

Experience

8-15+ years (Enterprise BI & Analytics focus)

Role Overview

We are seeking a Senior Data Engineer to build and manage modern Lakehouse-based data platforms that power Power BI-centric analytics across the enterprise. This role is aligned with best practices recommended by a Certified SAP BI/HANA Consultant with 22+ years of experience, including large-scale implementations in complex enterprise environments.

The ideal candidate will have strong expertise in Python, S3-compatible storage, and Lakehouse technologies, with hands-on experience integrating SAP HANA / SAP S/4HANA data into analytics-ready models optimized for Microsoft Power BI.

Key Responsibilities

Power BI-Focused Data Enablement
  • Design and deliver analytics-ready datasets optimized for Power BI performance and scalability.
  • Build and maintain semantic-friendly data models supporting DirectQuery, Import, and hybrid modes.
  • Ensure low-latency, high-reliability data access for dashboards and reports.
  • Partner with Power BI developers and business analysts to support enterprise reporting needs.
Lakehouse & Data Architecture
  • Design and implement Lakehouse architectures that serve as the single source of truth for analytics.
  • Combine data lake scalability with warehouse-style governance and performance.
  • Manage structured and semi-structured data using open table formats (Delta Lake, Iceberg, Hudi).
  • Support enterprise-scale analytics workloads and self-service BI.
SAP & Enterprise Source Integration
  • Ingest and transform data from SAP HANA, SAP S/4HANA, SAP BW, and related SAP systems.
  • Integrate SAP and non-SAP data sources into a unified analytics platform.
  • Optimize SAP-extracted data for downstream Power BI consumption.
  • Collaborate with SAP BI teams to modernize legacy reporting pipelines.
Data Engineering & Python Development
  • Develop scalable Python-based ETL/ELT pipelines.
  • Implement data transformations, validations, and enrichment logic.
  • Leverage distributed processing frameworks (e.g., Apache Spark).
  • Apply best practices in coding, testing, and deployment.
Storage, Cloud & Performance Optimization
  • Design and manage S3-compatible object storage (AWS S3, MinIO, Ceph).
  • Optimize storage layouts, partitioning, and file formats for BI query performance.
  • Implement cost management, data lifecycle, and archival strategies.
  • Ensure secure access, encryption, and compliance with enterprise standards.
Governance, Quality & Reliability
  • Implement data quality checks and monitoring aligned with BI SLAs.
  • Maintain data lineage, metadata, and auditability.
  • Ensure consistency between Lakehouse data and Power BI semantic layers.
  • Troubleshoot data freshness, performance, and accuracy issues.
Required Skills & Qualifications

Core Technical Skills
  • Strong proficiency in Python for data engineering.
  • Hands-on experience with Lakehouse technologies (Delta Lake, Apache Iceberg, Apache Hudi).
  • Strong experience with Power BI data modeling and performance optimization.
  • Advanced SQL skills across analytical workloads.
  • Experience working with S3-compatible object storage.
Power BI & Analytics Expertise
  • Deep understanding of Power BI:
    • Import vs DirectQuery vs Composite models
    • Performance tuning and dataset optimization
    • Semantic modeling best practices
  • Experience supporting enterprise-scale Power BI deployments.
  • Strong understanding of BI reporting, KPIs, and analytics workflows.
SAP & Enterprise Data
  • Experience integrating data from:
    • SAP HANA
    • SAP S/4HANA
    • SAP BW / BW on HANA
  • Understanding of SAP data models and enterprise reporting structures.
Preferred / Nice-to-Have Skills
  • Experience with Microsoft Fabric, Azure Data Lake, or Synapse.
  • Exposure to DAX optimization and Power BI capacity management.
  • Experience in oil & gas, manufacturing, or other regulated industries.
  • Knowledge of streaming platforms (Kafka, Kinesis).
  • Familiarity with orchestration tools (Airflow, Prefect).
  • Experience modernizing legacy SAP BI systems into cloud-native analytics platforms.
Education & Certifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • Power BI or Microsoft analytics certifications preferred.
  • SAP BI / HANA certification is a plus.
  • Cloud certifications (AWS, Azure) are advantageous.


Thanks, and regards,

Shashi Bhatt (she/her)

T: 517 974 7289 | Shashi@ricefwtech.com

www.ricefwtech.com

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