Informatica Data Quality Developer

Overview

Full Time

Skills

Informatica

Job Details

IDQ Developer

A data product comprises of team members with various skills, competencies, domain understandings, and process knowledge to build and support end to end life cycle of any Data Product

This require technical competencies or process skills that are specific to technology and domain being used, and some of these skills are core and will be applicable and relevant irrespective of the tool or application being used. E.g. Data Quality(DQ). A developer within data product would understand the concept of Data quality and would be able to identify DQ issues and suggests a mechanism to measure and resolve those. Similarly, if you consider Match process, modeling, etc. a very common functionality, a developer in data product team should be well versed in process.

Applications:

  • Informatica Product Suites: Informatica Data Quality (Cloud and On-Prem) used for building data quality mappings/routines that helps in data cleansing and data standardization in most efficient manner.
    • Development efficient & highly tuned data cleansing routines
    • Should be able to use all IDQ transformations including Address Doctors
    • Understands IDQ architecture and performance techniques with industry standard coding practices
    • Should be able to works with exposing data quality rules as webservices and consumed data from third party rest APIs
    • Should be able to work with managed and unmanaged reference table
    • Understands the code deployment & knows to automate it
    • Informatica Analyst Used by Business/ Data analyst & data stewards to profile data, define rule specification and manage business glossary
    • Build profile on heterogenous data sources Basic profiling, join data profiling
    • Build scorecards
    • Build reference tables
    • Build mapping and rule specifications
    • Build and manage Reference data though reference tables
    • Able to build and manage business glossary
    • Informatica Data Management Cloud Data Integration and Cloud Application Integration services are used for data integration and ETL flows and this helps our program with large scale integration projects with minimum infrastructure
    • Develop efficient & highly tuned data transformation mappings
    • Deploy and manage the secure agents
    • Utilize parametrization features in CDI/CAI
    • Build, execute/schedule mapping tasks and task flows
    • Performance tuning through lookup and other coding best practices
    • Knows SCD Types and its implementation in CDI/CAI
    • Rest API consumptions
    • Informatica Reference 360 Informatica's SaaS based product for reference data management
    • Build and implement code list
    • Build and implement cross walks
    • Access management on reference data
    • Ingest and export data in and out of Reference -360

  • Informatica MDM Resource Kit

    • Informatica Command Line Utilities
    • Informatica OOB API
    • Informatica Address Doctor
    • Apigee/Mulesoft/etc

  • Informatica platform administration

  • Informatica Patching/Upgrade utilities

  • Process Scheduling Application: Rundeck / Control-M
    • Build Jobs for execution of IDQ/ MDM processes
    • Build Jobs for execution of Database processes
    • Build Jobs for execution of Shell programs on Linux
    • Build Workflow Jobs and Daily batch processes
    • Setup Alerts/Notification/ Error handling Routines
    • Application Start/Stop Routines

  • Tools/ Utilities:
    • Linux Shell Scripting
    • Build Shell Programs for process executions
    • Application cleanup actions
    • SoapUI
    • Postman
    • CI/CD through Informatica Dev Ops Platform
    • Build Custom Operational Reports and Email Notifications
    • OS Infrastructure Alerts
    • Application Start/Stop routines

  • Documentation:
    • GIT Global Information Tracker
      • Strong Documentation Skills
      • Follow change management policies

  • Platform
    • Azure
  • Fundamental
  • Cloud computing
  • Databases
    • Oracle
  • Development
  • Project level administration
    • SQL Server, MYSQL
    • Exposure to NOSQL DBs Graph / Document Databases

Functional skills

  • Data Modeling
    • Logical / Physical Modeling

  • Data Integration
    • Batch & Realtime Integration
    • ETL

  • Master Data management
  • Data Governance
  • Business Definition of Data Elements
  • Understand Governance Rules and Policies for Master Data Entity
  • Data Lineage
  • Data Element Definition
  • Relationships Definition

  • Data Stewardship
  • Control Roles based Access to the master data
  • Implement approval / rejection process for create/Edit of master Data
  • Setup Business rules on Create/Edit of master data using IDD/E360 applications
  • Control Quality of Data as per defined Governance rules / Policies
  • Follow process for Manual Merges/ Unmerges

  • Data Quality
  • Match & Merge
  • Cross Referencing
  • BVT (Best Version of the Truth) and Survivorship Process
  • Project management skills:
  • Business Requirements Gathering
  • Logical Design / Technical Design
  • Estimation
  • Team management (For Leads)
  • Demo/Presentations