SAP

Forward Deployed Data Engineer

SAP$90K — $198K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's in Computer Science, Information Technology, Data Engineering, or relevant field.
  • 3-7 years of professional experience in data engineering or platform engineering.
  • Strong proficiency in SQL and Python programming.
  • Hands-on experience with Apache Spark, Databricks, Kafka, and Airflow.
  • Familiarity with enterprise data structures like data lakes and warehouses.
  • Knowledge of data governance, quality practices, and metadata management.
  • Experience in cloud environments (AWS, Azure, GCP) and microservices architecture.

Responsibilities

  • Design and implement scalable data pipelines for batch and real-time processing.
  • Build data ingestion frameworks for SAP and non-SAP systems.
  • Develop data models and semantic layers for AI applications.
  • Create ELT/ETL pipelines using SQL, Python, and Spark.
  • Ensure data quality and manage metadata processes effectively.
  • Develop APIs for data access by AI applications.
  • Optimize data storage and query performance across platforms.

Benefits

  • Flexible working hours due to hybrid work model.
  • Access to advanced training and development opportunities.
  • Comprehensive health benefits including medical and dental.
  • Employee wellness programs and initiatives.
  • Opportunities to work on cutting-edge AI technologies.
Full Job Description
Location: this is a hybrid position based from our New York City office located in the Hudson Yards.

What you'll build

As a Forward Deployed Data Engineer, you will design and implement modern enterprise data platforms that enable AI applications, analytics, and business processes. Working directly with customers, you will build scalable data pipelines, data models, semantic layers, and integrations across SAP and non-SAP systems. This role is intended for engineers with 3-7 years of experience who enjoy solving complex data challenges in customer-facing environments.

In this role, you will:
  • Design and implement scalable batch and real-time data pipelines.
  • Build data ingestion frameworks integrating SAP and non-SAP enterprise systems.
  • Develop logical and physical data models, semantic layers, and business schemas for AI applications.
  • Build ELT/ETL pipelines using SQL, Python, Spark, and modern data engineering frameworks.
  • Implement data quality, lineage, governance, metadata management, and validation processes.
  • Develop APIs and data services that expose enterprise data to AI agents and applications.
  • Optimize data storage, query performance, and distributed processing workloads.
  • Deploy and operate data platforms on SAP BTP, Kubernetes, hyperscalers, and cloud-native environments.
  • Collaborate with AI engineers, solution architects, and customer stakeholders to translate business requirements into robust data solutions.
  • Create reusable accelerators, reference data models, and engineering best practices.


What you bring
  • Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
  • 3-7 years of professional experience in data engineering or platform engineering.
  • Strong SQL and Python programming skills.
  • Hands-on experience with Apache Spark, Databricks, Kafka, Airflow, or similar modern data platforms.
  • Experience designing enterprise data models, data lakes, lakehouses, and data warehouses.
  • Experience with PostgreSQL, SAP HANA, Snowflake, BigQuery, or equivalent databases.
  • Knowledge of data governance, lineage, metadata management, and data quality practices.
  • Experience with Docker, Kubernetes, Git, CI/CD, and cloud platforms (AWS, Azure, or GCP).
  • Exposure to SAP Datasphere, SAP HANA Cloud, SAP Integration Suite, SAP BTP, or SAP AI Core is highly desirable.
  • Strong analytical thinking, customer engagement, and communication skills.


Nice to have
  • Experience supporting AI/ML workloads through feature stores, vector databases, or embedding pipelines.
  • Knowledge of Knowledge Graphs, GraphRAG, or semantic technologies.
  • Experience with dbt, Iceberg, Delta Lake, or Apache Flink.
  • Open-source contributions or experience with AI-assisted engineering tools such as GitHub Copilot or Cursor.


Compensation Range Transparency: SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward demonstrating SAP's commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted annual combined range for this position is [redacted]00USD. The actual amount to be offered to the successful candidate will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. Any SAP variable incentive includes a targeted dollar amount and any actual payout amount is dependent on company and personal performance. Please reference this link for a summary of SAP benefits and eligibility requirements: SAP North America Benefits.

AI Usage in the Recruitment Process

For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.

Please note that any violation of these guidelines may result in disqualification from the hiring process.

Requisition ID: 457466 | Work Area: Software-Design and Development | Expected Travel: 0 - 70% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid

Requisition ID: 457466

Posted Date: Aug 2, 2026

Work Area: Software-Design and Development

Career Status: Professional

Employment Type: Regular Full Time

Expected Travel: 0 - 70%

Location:

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