We are seeking a Data Engineer to support data validation, reconciliation, and reporting for a finance data platform modernization initiative. This role focuses on identifying variances between legacy and modern systems, helping improve data quality, and supporting go-live readiness through clear analysis and collaboration across technical and business teams.

Responsibilities

• Build and run queries to compare legacy and modern datasets and identify data variances.
• Create reports and dashboards to highlight discrepancies, trends, and reconciliation results.
• Support source-to-target reconciliation, duplicate detection, control total checks, and business rule validation.
• Analyze mapping documents, reporting requirements, transformation logic, and data lineage to support validation efforts.
• Document variances, root causes, exception findings, defect logs, and sign-off materials in partnership with stakeholders.
• Collaborate with product, engineering, finance, business, and legacy system teams to resolve issues and support go-live decisions.
• Assist with determining tolerance thresholds and readiness for parallel operations and production launch.
• Contribute to iterative delivery in an agile environment, including sprint ceremonies and defect triage.

Skills

• 5+ years of hands-on SQL experience with big data platforms or databases such as Google BigQuery, Hadoop, or similar tools.
• Strong background in ETL and data pipeline tools such as Dataproc, Airflow, Dataform, dbt, or comparable technologies.
• Experience using Python and/or PySpark for data movement, analysis, and validation.
• Proven experience in data analysis, data quality validation, and reconciliation across systems.
• Ability to work with visualization and reporting tools such as Power BI, Looker, or LookML.
• Strong communication and collaboration skills with the ability to work across technical and business teams.
• Experience creating documentation that supports validation, issue tracking, and business approvals.
• 5+ years working in a data analytics role.
• 1–3 years of experience working on agile teams.

Preferred Skills

• Experience in the retail industry, especially across finance, supply chain, merchandising, inventory, stores, sales, digital, product, or customer domains.
• Familiarity with Google Cloud medallion data architecture and GCP-supported data processing tools.
• Experience with SAP S/4 data structures and finance reporting.
• Background supporting dashboard development, KPI reconciliation, and semantic layer validation.
• Experience working in a modern data platform migration or parallel run environment.
• Comfort working in a fast-paced, collaborative setting with evolving priorities.

Horizontal is committed to creating an inclusive environment where diverse perspectives are valued and everyone has the opportunity to thrive. We welcome candidates from all backgrounds and are dedicated to equity, belonging, and respect throughout the hiring process.

By applying for this position, you acknowledge and agree that Horizontal Talent may contact you regarding your application using automated technology, including phone calls, SMS/text messages, or email, which may be delivered by our virtual AI recruiter, Alex.