SAP/ERP Transformation - Principal Data Engineer

Loyalty360

Salisbury (NC)

Hybrid

USD 163,000 - 245,000

Full time

14 days+
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Job summary

Ahold Delhaize USA in Salisbury, NC is seeking a Senior SAP Data Conversion Lead to design and implement end-to-end data migration patterns for SAP, using SAP BODS, Data Services, and cloud-enabled pipelines.

You will collaborate with data analysts, SAP teams, and vendors to deliver auditable ETL processes, ensure data quality, governance, and security, and guide complex program decisions while supporting critical incident responses.

Qualifications

  • Bachelor's degree or equivalent years of work experience.
  • 10+ years in data engineering with large scale systems.
  • Proficiency in distributed data processing, orchestration, and storage patterns.
  • Strong automation/scripting skills and version control practices.
  • Excellent cross team communication and influence.
  • Demonstrated experience leading complex SAP data conversion and migration workstreams across master and transactional data objects.
  • Advanced hands‑on expertise with SAP BODS, including job design, workflows, data stores, transformations, debugging, performance tuning, scheduling, and migration across environments.
  • Strong SQL, relational database, data mapping, profiling, reconciliation, ETL pipeline development, data quality, stewardship, governance, lineage, and audit-control skills.
  • Proven ability to collaborate with analysts, SAP functional teams, engineers, business stakeholders, and external vendors to convert requirements into executable technical solutions.
  • Demonstrated experience designing, developing, testing, and operating distributed data pipelines using Apache Spark, SQL, and a modern programming language such as Python or Scala.
  • Experience with Databricks and modern cloud data engineering platforms, working with systems integrators , and governing vendor-delivered technical artifacts.

Responsibilities

  • Design reusable patterns for batch and streaming ingestion, transformations, and data product delivery, optimizing for performance and scale.
  • Build automation for quality, lineage, and governance checks integrated into CI/CD, including deployment scripts and pipeline templates that reduce manual effort.
  • Create and evolve internal tooling, developer platforms, and golden paths that improve reliability and time-to-delivery for data teams.
  • Harden security and privacy controls (access, encryption, masking) across platforms and pipelines, integrating controls into automated delivery workflows.
  • Elevate reliability with SLOs, telemetry, monitoring/logging/tracing, and automated rollback/reprocessing; contribute to observability implementations (e.g., DataDog).
  • Integrate and optimize cloud services and container orchestration where relevant to improve scalability and reduce operational toil.
  • Maintain infrastructure as code and repeatable environments using tools such as Terraform, Ansible, or CloudFormation.
  • Guide solution decisions for complex programs; run technical reviews and threat/quality modeling to ensure robust outcomes.
  • Document standards, playbooks, and reusable components to reduce rework and improve consistency across teams.
  • Coach teams on data modeling, performance optimization, and design thinking for data consumer experience.
  • May be called upon to support critical escalations and must be available during urgent IT incidents as needed.
  • Lead end-to-end SAP data conversion across extraction, profiling, cleansing, mapping, harmonization, transformation, validation, reconciliation, and load activities.
  • Design, build, test, tune, and maintain SAP BODS jobs, workflows, data stores, reusable transformations, exception handling, and deployment components for mock conversions and production cutover.
  • Work with data analysts, SAP functional teams, and business data owners to translate data-object requirements, mappings, and transformation rules into complete, testable ETL specifications.
  • Coordinate technical delivery with implementation vendors and consulting partners, including reviewing designs and code, resolving dependencies and defects, and ensuring deliverables meet internal engineering standards.
  • Establish automated data-quality controls, reconciliation checks, lineage, audit evidence, monitoring, and exception-management processes to ensure complete and accurate migration results.
  • Plan and support conversion rehearsals, mock loads, cutover execution, rollback and reprocessing procedures, post-load validation, and root-cause remediation across legacy systems and SAP.

Skills

SQL
Python/Scala
Apache Spark
ETL pipelines
Data modeling
Data governance

Education

Bachelor's degree in CS/Engineering or equivalent
10+ years data engineering experience

Tools

SAP BODS
Databricks
Terraform
Ansible
CloudFormation

Job description

Category/Area of Expertise: Data-Science & Analytics

Job Requisition: 537786

Address: USA-NC-Salisbury-2110 Executive Drive

Store Code: IT Executive & Administration (5169193)

Ahold Delhaize USA, a division of global food retailer Ahold Delhaize, is part of the U.S. family of brands, which includes five leading omnichannel grocery brands - Food Lion, Giant Food, The GIANT Company, Hannaford and Stop & Shop. Our associates support the brands with a wide range of services, including Finance, Legal, Sustainability, Commercial, Digital and E-commerce, Technology and more.

Primary Purpose:

Senior technical authority who designs reference architectures and reusable patterns for data ingestion, transformation, storage, and delivery-embedding automation, observability, and security into every stage.

Serves as the hands‑on SAP Transformation Data Conversion Lead, accountable for the engineering approach to extracting, cleansing, harmonizing, transforming, validating, and loading enterprise data into SAP. Partners with data analysts, business data owners, internal engineering teams, and implementation vendors to deliver clean, controlled, auditable ETL pipelines using SAP BusinessObjects Data Services (BODS) and related platforms.

*Our flexible/hybrid work schedule includes 3 in-person days at one of our core locations and 2 remote days. Our core office location for this role is Salisbury, NC.

*Applicants must be currently authorized to work in the United States on a full-time basis.

Duties and Responsibilities:
  • Design reusable patterns for batch and streaming ingestion, transformations, and data product delivery, optimizing for performance and scale.
  • Build automation for quality, lineage, and governance checks integrated into CI/CD, including deployment scripts and pipeline templates that reduce manual effort.
  • Create and evolve internal tooling, developer platforms, and golden paths that improve reliability and time-to-delivery for data teams.
  • Harden security and privacy controls (access, encryption, masking) across platforms and pipelines, integrating controls into automated delivery workflows.
  • Elevate reliability with SLOs, telemetry, monitoring/logging/tracing, and automated rollback/reprocessing; contribute to observability implementations (e.g., DataDog).
  • Integrate and optimize cloud services and container orchestration where relevant to improve scalability and reduce operational toil.
  • Maintain infrastructure as code and repeatable environments using tools such as Terraform, Ansible, or CloudFormation.
  • Guide solution decisions for complex programs; run technical reviews and threat/quality modeling to ensure robust outcomes.
  • Document standards, playbooks, and reusable components to reduce rework and improve consistency across teams.
  • Coach teams on data modeling, performance optimization, and design thinking for data consumer experience.
  • May be called upon to support critical escalations and must be available during urgent IT incidents as needed.
  • Lead end-to-end SAP data conversion across extraction, profiling, cleansing, mapping, harmonization, transformation, validation, reconciliation, and load activities.
  • Design, build, test, tune, and maintain SAP BODS jobs, workflows, data stores, reusable transformations, exception handling, and deployment components for mock conversions and production cutover.
  • Work with data analysts, SAP functional teams, and business data owners to translate data-object requirements, mappings, and transformation rules into complete, testable ETL specifications.
  • Coordinate technical delivery with implementation vendors and consulting partners, including reviewing designs and code, resolving dependencies and defects, and ensuring deliverables meet internal engineering standards.
  • Establish automated data-quality controls, reconciliation checks, lineage, audit evidence, monitoring, and exception-management processes to ensure complete and accurate migration results.
  • Plan and support conversion rehearsals, mock loads, cutover execution, rollback and reprocessing procedures, post-load validation, and root-cause remediation across legacy systems and SAP.
Qualifications:
  • Bachelor's degree or equivalent years of work experience.
  • 10+ years in data engineering with large scale systems.
  • Proficiency in distributed data processing, orchestration, and storage patterns.
  • Strong automation/scripting skills and version control practices.
  • Excellent cross team communication and influence.
  • Demonstrated experience leading complex SAP data conversion and migration workstreams across master and transactional data objects.
  • Advanced hands‑on expertise with SAP BusinessObjects Data Services (BODS), including job design, workflows, data stores, transformations, debugging, performance tuning, scheduling, and migration across environments.
  • Strong SQL, relational database, data mapping, profiling, reconciliation, ETL pipeline development, data quality, stewardship, governance, lineage, and audit-control skills.
  • Proven ability to collaborate with analysts, SAP functional teams, engineers, business stakeholders, and external vendors to convert requirements into executable technical solutions.
  • Demonstrated experience designing, developing, testing, and operating distributed data pipelines using Apache Spark, SQL, and a modern programming language such as Python or Scala.
  • Experience with Databricks and modern cloud data engineering platforms, working with systems integrators , and governing vendor-delivered technical artifacts.
Preferred Qualifications:
  • Experience with feature stores and ML ready data patterns.
  • Knowledge of cost optimization and workload right sizing.
  • Experience supporting a large-scale SAP S/4HANA implementation, transformation, or multi-wave migration program.
  • Deep hands‑on expertise with Databricks and modern lakehouse architecture, including Spark-based processing, Delta Lake, orchestration, governance, performance optimization, and production operations.

Salary Range NC: $163,280 - $244,920

Actual compensation offered to a candidate may vary based on their unique qualifications and experience, internal equity, and market conditions. Final compensation decisions will be made in accordance with company policies and applicable laws.

#LI-RC1 #LI-Hybrid

At Ahold Delhaize USA, we provide services to one of the largest portfolios of grocery companies in the nation, and we're actively seeking top talent.

Our team shares a common motivation to drive change, take ownership and enable our brands to better care for their customers. We thrive on supporting great local grocery brands and their strategies.

Our associates are the heartbeat of our organization. We are committed to offering a welcoming work environment where all associates can succeed and thrive. Guided by our values of courage, care, teamwork, integrity (and even a little humor), we are dedicated to being a great place to work.

We believe in collaboration, curiosity, and continuous learning in all that we think, create and do. While building a culture where personal and professional growth are just as important as business growth, we invest in our people, empowering them to learn, grow and deliver at all levels of the business.

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