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Data Engineer

Location

Greater Bengaluru Area

JobType

full-time

About the job

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About the role

JSAN Consulting Group

Website: jsanconsulting.com
Job details:

🚨 Critical Hiring – Immediate Joiners Required! 🚨


Role: Data Engineer


📍 Location: Bangalore


  • Shift : US shift (02:00 PM to 11:00 PM IST)
  • Mode : Hybrid


🕑 Availability: Immediate Joiners - 30 days


📧 Interested Candidates? Apply Now!


Send your CV to: askiranmayi@jsanconsulting.com


WhatsApp: 9880225770


🔑 Key Responsibilities


Product Data Quality & MDM Implementation – Responsibilities
1. Data Profiling & Quality Assessment (Informatica IDMC)


  • Perform end-to-end data profiling across Product domain systems:
  • JDE (F4101, F4102)
  • Syndigo Product Catalog
  • Sphera Regulatory Data
  • Execute all five profiling stages using Informatica IDMC:
  1. Structure Discovery – Analyze schema, datatypes, patterns
  2. Content Discovery – Assess completeness, uniqueness, nulls
  3. Relationship Discovery – Identify joins, PK–FK relationships
  4. Data Rule Discovery – Infer implicit validation rules
  5. Business Context Analysis – Align data with business meaning


2. System Inventory & Cross-System Analysis


  • Build and maintain the Product Domain System Inventory Register, capturing:
  • Source systems, tables, attributes, owners, refresh frequency
  • Conduct cross-system attribute comparison:
  • Identify conflicts (e.g., different UOMs, naming inconsistencies)
  • Identify gaps (missing attributes across systems)
  • Compare JDE vs Syndigo for:
  • Product descriptions
  • GTIN alignment
  • Taxonomy/category mismatches

  • 3. Data Quality Scorecard & Root Cause Analysis


    • Develop a baseline Data Quality (DQ) Scorecard:
    • Completeness
    • Accuracy
    • Consistency
    • Uniqueness
    • Validity
    • Perform root cause classification:
    • Source system issue
    • Transformation issue
    • Manual entry error
    • Integration gaps
    • Assign business impact scores per attribute:
    • High (regulatory / customer-facing)
    • Medium (operational)
    • Low (informational)


    4. Data Quality Rule Definition


    Translate profiling insights into implementable DQ rules:


    Validation Rules


    • GTIN must be 8/12/13/14 digits with valid checksum
    • HSN codes must match standard classification formats
    • UOM must exist in approved reference list


    Standardization Rules


    • Normalize product descriptions (case, abbreviations)
    • Standardize UOMs (e.g., KG vs Kilogram)


    Enrichment Rules


    • Populate missing taxonomy using Syndigo hierarchy
    • Derive attributes (e.g., pack size, category)


    Matching Rules


    • Identify duplicate products using:
    • GTIN
    • Description similarity
    • Manufacturer + SKU


    Survivorship Rules


    • Define system priority:
    • Syndigo (marketing attributes)
    • JDE (transactional attributes)
    • Sphera (regulatory attributes)


    5. MDM Support (Product Domain)


    • Support MDM Architect in defining:
    • Product data lifecycle state machineDraft → Enriched → Validated → Published → Retired
    • Attribute-to-logical model mappings
    • Golden record definition
    • Create data collection & cleansing templates for business users:
    • Excel/web forms with validation rules
    • Mandatory field enforcement


    6. Governance & Validation


    • Participate in Domain Owner validation cycles
    • Provide technical evidence for System of Record (SoR) decisions:
    • Profiling outputs
    • DQ metrics
    • Conflict analysis
    • Ensure:
    • All findings are reviewed
    • Sign-offs are obtained
    • Inputs are finalized before Blueprint phase completion


    Required Skills & Expertise


    Core Technical Skills


    • SQL (advanced querying, profiling, joins, aggregations)
    • Data Warehousing Concepts (dimensional modeling, ETL)
    • Informatica IDMC:
    • Data Profiling
    • Data Quality transformations
    • Rule specification


    Integration & Tools


    • Informatica Data Integration (ETL pipelines)
    • Experience with:
    • JDE (JD Edwards) – Product master tables (F4101/F4102)
    • Syndigo – Product content management
    • Sphera – Regulatory/compliance datasets


    Nice-to-Have


    • Master Data Management (MDM) tools/processes
    • Data Governance frameworks
    • Product taxonomy & classification knowledge
    • Regulatory data handling (e.g., compliance attributes)


    Outcome Deliverables


    • Product System Inventory Register
    • Cross-system attribute comparison report
    • Data Quality Scorecard
    • Defined DQ rules repository
    • Product lifecycle model
    • Signed-off SoR decisions



    Click on Apply to know more.

    Skills

    content management
    compliance
    data engineer
    end-to-end
    ETL
    product lifecycle
    Root Cause Analysis
    specification
    SQL