Role description

DQ Architecture Automation Lead

Purpose Design the futurestate automated DQ framework

Your recent discussion highlighted the need for automation of

Inventory management

Rule monitoring

Governance reporting

Severity categorization

Risk prioritization

Key Responsibilities

Define technical architecture

Evaluate Collibra Immuta and other candidate solutions

Design integrated DQ platform strategy

Define metadata and lineage architecture

Build automation patterns and reusable frameworks

Establish technical standards

Required Skills

Data architecture

Metadata management

Data lineage

Cloud and data platforms

API integration

Desired Skills

Collibra

Starburst

Data observability platforms

AIMLbased monitoring

Other details

Work within an agile team to remediate Data Quality gaps

while designing to deliver a proactive governed endto end

ADS data ecosystem with automated controls clear

ownership realtime monitoring and scalable

governance

Works with technology partners and a diverse set of

stakeholders to identify and close gaps in data

management standards adherence negotiates paths

forward and helps identify and communicate solutions to

complex data problems leveraging knowledge of

information systems techniques and processes

Implement and maintain data quality frameworks and

techniques in large data warehouse environments to

ensure data integrity

Codes complex solutions to integrate clean transform

and control data builds processes supporting data

transformation data structures metadata data quality

controls dependency and workload management

assembles complex data sets and communicates

required information for deployment