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SAP/ERP Transformation - Principal Data Engineer

Ahold Delhaize USA

Salisbury, USA

Full-time

Senior · 10+ years experience

Hybrid

USD 163280-244920 yearly / year

Discovered 1 weeks ago

SAP BusinessObjects Data Services (BODS)DataDogTerraformAnsibleCloudFormationApache Spark

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SAP BusinessObjects Data Services (BODS)DataDogTerraform

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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.
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.
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.