Role: Data Analyst with ERP, Data Modeling, GCP, SQL

Location: Jersey City; NJ – Day 1 Onsite

Duration: longterm – 15 months +

Overall Exp. Level: 9 to 15 Yreas.

Skills & Description:

Data Analyst with ERP Experience (any ERP will work) from ( any module - Sales, Finance, Operation, Maufacturing, Supply Chan) with PLSQL or SQL Query & Cloud Exp. on GCP. Data Modelling or MDM Exeperience.

Key Responsibilities

Requirement Gathering & Mapping: Partner with Sales, Finance, and Operations SMEs to understand business requirements, identify critical data elements, and document source-to-target mappings (STTM) for the GCP Data Lake.

Canonical Data Modeling: Collaborate with SMEs and data architects to define and document the enterprise canonical model, ensuring standard definitions, naming conventions, and data types across different domains.

 Technical Specifications: Translate business logic and KPIs into rigorous technical requirements, user stories, and acceptance criteria for the GCP Data Engineering team.

 Gap & Impact Analysis: Profile source data to identify data quality issues, anomalies, and structural gaps between legacy sources and the target canonical model.

 KPI & Data Validation: Define the testing and validation criteria to ensure that migrated data accurately populates downstream business KPIs. Perform UAT (User Acceptance Testing) to sign off on engineered data pipelines.

 Data Governance & Documentation: Maintain the data dictionary, business glossary, and lineage metadata within our data catalog tool (e.g., GCP Dataplex)

Required Skills & Qualifications

Experience: 4+ years of experience as a Data Analyst, Business Systems Analyst, or Data Product Owner, with a proven track record in Data Lake, Data Warehouse, or MDM (Master Data Management) implementations.

Domain Knowledge: Proven experience working with data domains in Sales (e.g., CRM, pipelines), Finance (e.g., ERP, general ledger), and/or Operations.

 Technical Skills:

 Advanced SQL: Ability to write complex queries to profile data, analyze schemas, and validate pipeline outputs.

 Data Modeling: Solid understanding of data modeling concepts (e.g., Star Schema, Snowflake, Inmon vs. Kimball, and Canonical/Universal modeling).

 Cloud Exposure: Familiarity with cloud data concepts. Direct experience with Google Cloud Platform (BigQuery, Cloud Storage, Dataplex) is highly preferred.