Data Engineer

LanceSoft, Inc. is a prominent staffing firm in the US, and they are seeking a Data Engineer to support data validation and reconciliation for Finance data platforms. The role involves identifying data variances, collaborating with teams, and developing reports and dashboards for data analysis.

Responsibilities:

• Support data validation, data reconciliation, and reports development for the Finance mainframe application modernization and data platform migration to modern GCP-based data platform
• Identify data variance between legacy and modern platforms for modern Finance applications and 2 quarter parallel operation
• Collaborate with product and business teams to identify root causes for the variances and resolve/document the variance to assist on Go-Live decision
• Develop queries and dataset required to validate legacy vs modern applications datasets to identify data variances
• Develop reports using end user visualization tools to present the variances and trends between sources
• Document data variances and identified root causes in collaboration with Product Manager/Engineers/Business Teams and get business sign off for known variances
• Build dashboards for data variance trend for the stakeholders and assist on determining tolerance thresholds for Go Live decisions

Requirements:

• Senior level (5+ years) hands-on SQL experience with big data platforms/databases like Google BigQuery, Hadoop or similar data platform
• Senior experience with ETL and data pipeline tools such as Dataproc, Airflow, Dataform, dbt, or similar tools
• Good experience with Python/Pyspark coding for data movement and analysis
• Experience with data visualization and reporting tools such as Power BI, Looker, and LookML for dashboard development, KPI reconciliation, semantic layer validation, and data analysis
• Strong experience in data analysis, data validation, source-to-target reconciliation, duplicate detection, reject/error validation, audit/control total validation, and business rule validation
• Ability to analyze mapping documents, reporting requirements, transformation logic, data lineage, and data quality rules
• Experience creating reconciliation reports, validation summaries, exception reports, defect logs, and business sign-off documentation
• Strong communication and collaboration skills with the ability to work closely with engineering, product, finance, business, and legacy system teams
• 5+ years working in data analytics role
• 1–3 years of experience working in agile team
• Prior retail industry experience, especially working with large enterprise data in finance, supply chain, merchandising, inventory, stores, sales, digital, product, or customer domains
• Experience working with Google Cloud Medallion Data Layer and GCP supported data processing tools
• Familiarity with SAP S4 data structure and finance domain report building experience
• Experience working in agile delivery environments, including user stories, acceptance criteria, sprint ceremonies, defect triage, and iterative delivery