POSITION SUMMARY

The Internal Audit Data Analytics team is seeking experienced Data Engineer to support the buildout and ongoing enhancement of Internal Audits Databricks-based analytics environment. This role will focus on designing building and maintaining scalable data pipelines and data lake solutions used to support standalone audits continuous auditing and risk monitoring initiatives across the enterprise.

Reporting to the Data Analytics Sr. Manager Internal Audit the Data Engineers will play a critical role in enabling high-quality governed and automated data flows into Internal Audits Databricks cube. This position will partner closely with auditors data analysts IT organization and business stakeholders to ensure reliable data ingestion data quality and availability of analytical datasets for use in audit execution risk assessments and strategic data-driven initiatives.

This is a hands-on engineering role requiring deep technical expertise in Databricks cloud platforms (Azure preferred) data modeling ETL/ELT design and development of scalable data engineering solutions.

PRIMARY DUTIES AND RESPONSIBILITIES

Data Engineering & Pipeline Development

• Design build and maintain large-scale fault-tolerant data pipelines using Python/PySpark Databricks Delta Lake and orchestration tools (e.g. Airflow Azure Data Factory).

• Develop and optimize ETL/ELT workflows to support ingestion transformation and modeling of large datasets into a Lakehouse using Delta Lake: batch ingestion from files databases APIs; streaming using Structured Streaming; handling semi-structured data (JSON Parquet Avro); ELT patterns using Spark SQL / PySpark; Incremental processing patterns; Databricks Jobs; External orchestrators (ADF Airflow etc.)

• Handson experience with SAP ECC or SAP S/4HANA data extraction and processing

• ImplementCDC incremental loads and full refresh patterns; handle schema evolution and data reconciliation.

• Develop and maintain curated data models (bronze/silver/gold) and support BI/analytics consumption.

• Optimize performance and cost (partitioning Z-ORDER file sizing caching cluster policies job tuning).

• Implement scalable data lake and analytical platform architectures on Azure ensuring security governance and cost efficiency.

• Automate repeatable ingestion processes using infrastructure as code (IaC) and Continuous Integration (CI)/Continuous Delivery (CD) deployment methodologies.

• Develop robust data models and semantic layers to facilitate analytical consumption by auditors and Data Analytics teammates.

Data Quality Monitoring & Governance

• Create and manage data quality checks anomaly detection routines and automated alerting to ensure accuracy and integrity of audit datasets and SLA-driven operations.

• Establish repeatable processes for documenting data lineage validation reconciliation and test coverage.

• Implement scalable frameworks for metadata management schema validation and versioning of data pipelines.

Audit Collaboration & Analytics Support

• Support IA audit execution by enabling access to clean reliable and well-documented datasets.

• Provide SME-level guidance on data availability data structures pipeline behavior and data limitations.

Standards Innovation & Best Practices

• Establish consistency in design patterns coding approaches documentation and engineering standards.

• Identify opportunities to modernize or optimize existing pipelines architecture or data processing patterns.

• Contribute to the continuous improvement of the Internal Audit analytics program through automation performance tuning and new capability development.

• Create and maintain technical documentation runbooks and onboarding guides.

• Participate in code reviews and promote engineering best practices (testing CI/CD version control).

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EXPERIENCE AND EDUCATIONAL REQUIREMENTS

• Bachelors or Masters degree in Computer Science Data Engineering Information Systems Analytics or related discipline; equivalent work experience considered.

• Minimum 35 years of relevant experience required; 57 years preferred including 2-4 years of hands-on Data Engineering experience with Databricks.

• Build and manage scalable ETL/ELT pipelines integrating data from SAP ECC or SAP S/4HANA.

• Deep expertise working with Databricks including cluster design notebook development Spark optimization Delta Lake Delta Live Tables Unity Catalog (Centralized permissions Data lineage Table & schema access controls) and data governance/access controls.

• Strong proficiency in Python PySpark/Spark and SQL; understanding of Spark architecture: Driver Executors Stages Tasks and Shuffle portioning caching. Performance tuning and optimization on large datasets.

• Experience designing and managing large-scale data ingestion from complex enterprise systems (ERP financial systems operational platforms).

• Hands-on experience with Azure (preferred) Amazon Web Services (AWS) or Google Cloud Platform (GCP) cloud services.

• Solid understanding of data warehousing/Lake house concepts Delta Lake (Delta Lake table design ACID transactions schema enforcement & evolution time travel handling late arriving data) and medallion architecture.

• Experience in creating and supporting end-to-end ETL/ELT workflows.

• Experience handling semistructured data (JSON Parquet Avro).

• Prior experience developing semantic models for analytics consumption.

• Strong experience with data quality frameworks validation routines and monitoring strategies.

• Experience with Git-based development and CI/CD practices.

• Experience with cloud storage and services (Azure Data Lake Storage).

• Experience with data integration tools (e.g. Fivetran ADF etc).

• Experience collaborating with US-based onshore teams is strongly preferred.

• Databricks Data Engineer Professional or Associate Certification is preferred.

• Azure Data Engineer Associate (DP203) Certification is preferred

What Cencora offers

Benefit offerings outside the US may vary by country and will be aligned to local market practice. The eligibility and effective date may differ for some benefits and for team members covered under collective bargaining agreements.

Affiliated Companies

Equal Employment Opportunity

Cencora is committed to providing equal employment opportunity without regard to race color religion sex sexual orientation gender identity genetic information national origin age disability veteran status or membership in any other class protected by federal state or local law.

The companys continued success depends on the full and effective utilization of qualified individuals. Therefore harassment is prohibited and all matters related to recruiting training compensation benefits promotions and transfers comply with equal opportunity principles and are non-discriminatory.

Cencora is committed to providing reasonable accommodations to individuals with disabilities during the employment process which are consistent with legal requirements. If you wish to request an accommodation while seeking employment please call 888.692.2272 or email . We will make accommodation determinations on a request-by-request basis. Messages and emails regarding anything other than accommodations requests will not be returned