Data Engineer

Data Analyst – Finance Data Platform

Purpose: Support data validation, data reconciliation, and reports development for the Finance mainframe application modernization and data platform migration to modern GCP-based data platform. Outcome: 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.

Core Skill: 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. Experience with Python/Pyspark coding for data movement and analysis.

• 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.

Preferred Skillset:

• 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.

General requirements:

• 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.
• 5+ years working in data analytics role.
• 1–3 years of experience working in agile team.

Employee Benefits:

• Four options of medical Insurance
• Dental and Vision Insurance
• 401k Contributions
• Critical Illness Insurance
• Voluntary Permanent Life Insurance
• Accident Insurance
• Other Employee Perks

About LanceSoft:

LanceSoft is rated as one of the largest staffing firms in the US by SIA. Our mission is to establish global cross-culture human connections that further the careers of our employees and strengthen the businesses of our clients. We are driven to use the power of our global network to connect businesses with the right people, and people with the right businesses without bias. We provide Global Workforce Solutions with a human touch.