Role: BI / Data Operations Domain
Location: Sydney, NSW
Experience: 10+ years
Role type: Permanent

Role Summary:

• We are looking for an experienced BI / Data Opera=ons Domain Manager to lead and manage enterprise-scale BI, data warehouse, campaign, decisioning and data opera=ons plaDorms.
• The role requires strong technical and managerial understanding of Teradata Data Warehouse, SAS DI, SAS CI, SAS RTDM, AWS RedshiJ, AWS Glue, Apache Airflow, DAG-based orchestra=on, Qlik and related BI/data ecosystem components.
• The candidate will be responsible for ensuring the stability, reliability, availability, data freshness, orchestra=on health, SLA adherence and opera=onal governance of businesscri=cal data plaDorms. The role requires strong business-facing capability to work with stakeholders across technology, analy=cs, campaign, repor=ng and opera=ons teams.
• The role is especially suited for a senior data opera=ons leader who can manage both legacy enterprise BI plaDorms such as Teradata/SAS/Qlik and modern cloud data plaDorms such as AWS RedshiJ, AWS Glue and Airflow-based orchestra=on.
• Telecom domain experience is highly desirable, especially with exposure to BSS/OSS, CRM, billing, campaign management, customer analy=cs, CDR, network, revenue, product and customer data. Exis=ng internal references men=on Teradata, SAS, RTDM and Qlik usage in telecom BI/data environments.
• Key Responsibilities

1. BI & Data Opera=ons Leadership

Lead end-to-end opera=ons for BI, data warehouse, analy=cs, campaign and repor=ng

plaDorms.

Manage daily, weekly and monthly opera=onal cycles across ETL, ELT, batch, near-real-=me,

repor=ng, campaign and decisioning workloads.

Ensure produc=on stability across inges=on pipelines, transforma=on jobs, data marts,

dashboards, regulatory extracts and downstream data feeds.

Own opera=onal readiness for new releases, source changes, data model changes, plaDorm

upgrades, migra=on ac=vi=es and business-cri=cal deployments.

Provide leadership across L2/L3 support teams, data engineers, BI developers, SAS specialists,

data analysts, cloud data engineers and opera=ons teams.

Drive opera=onal discipline across incident, problem, change, release, deployment,

monitoring and stakeholder communica=on processes.

2. Data Warehouse & BI PlaDorm Management

Manage and govern enterprise data warehouse opera=ons across Teradata, AWS RedshiJ and

associated BI/data plaDorms.

Oversee data loads, batch schedules, source-to-target flows, transforma=on logic, data marts,

seman=c layers and report availability.

Ensure performance, scalability and availability of cri=cal data warehouse workloads.

Monitor database performance, workload concurrency, long-running queries, failed loads,

capacity constraints and data processing windows.

Work with DBA, data engineering, infrastructure and cloud plaDorm teams to resolve

performance boYlenecks and data load failures.

Support moderniza=on and coexistence between legacy data warehouse plaDorms and cloudbased plaDorms such as AWS RedshiJ. Exis=ng internal JD references men=on data

warehousing experience across Teradata, SAS and AWS in BI/telecom contexts.

3. AWS Glue & Cloud Data Opera=ons

Manage and support AWS Glue-based ETL/ELT pipelines used for inges=on, transforma=on,

data prepara=on and downstream data processing.

Oversee Glue jobs, crawlers, job schedules, job dependencies, failures, retries and opera=onal

monitoring.

Ensure AWS Glue pipelines are aligned with business-cri=cal data processing windows and

repor=ng SLAs.

Work with data engineering teams to support pipeline op=miza=on, error handling,

restartability, dependency handling and opera=onal resilience.

Monitor Glue job execu=on, data movement, transforma=on failures, schema changes and

downstream data availability.

Support cloud data warehouse integra=on paYerns involving AWS Glue, AWS RedshiJ, S3-

based data staging and downstream repor=ng plaDorms.

Ensure strong opera=onal controls around cloud data processing, including data

completeness, reconcilia=on, logging, aler=ng and escala=on.

4. Apache Airflow / DAG Orchestra=on Management

Manage and govern Airflow-based orchestra=on for business-cri=cal data pipelines.

Oversee DAG schedules, task dependencies, upstream/downstream job flows, retries, SLA

misses and failure handling.

Ensure DAGs are designed and operated with clear dependency management, restartability

and monitoring controls.

Track DAG execu=on health across inges=on, transforma=on, data quality, repor=ng and

extract delivery workflows.

Coordinate with engineering teams to resolve failed DAG runs, blocked tasks, dependency

failures and delayed data availability.

Review opera=onal readiness of new DAGs before produc=on deployment.

Ensure proper naming standards, documenta=on, aler=ng, ownership and support model for

Airflow DAGs.

Drive improvements in orchestra=on reliability, including beYer dependency mapping,

automated recovery, proac=ve alerts and opera=onal dashboards.

5. SAS PlaDorm Opera=ons – SAS DI, SAS CI & SAS RTDM

Manage opera=onal support and delivery across the SAS ecosystem, including:

SAS DI for ETL/data integra=on workflows

SAS CI for campaign management and customer engagement o SAS RTDM for real-=me

decisioning and customer interac=on use cases

Ensure SAS jobs, flows, campaigns and decisioning processes run as per agreed business

schedules.

Support inves=ga=on and resolu=on of SAS job failures, campaign data issues, RTDM

decisioning issues and dependency failures.

Coordinate with business teams on campaign readiness, audience data availability,

segmenta=on accuracy and decisioning plaDorm stability.

Ensure robust controls around campaign data extracts, eligibility logic, customer targe=ng

data, suppression rules and opera=onal valida=ons.

Prior internal templates reference SAS DI, SAS, RTDM, Teradata and related

deployment/support ac=vi=es.

6. Qlik / BI Repor=ng Opera=ons

Manage availability and reliability of dashboards, reports, extracts and businessfacing

analy=cs outputs.

Support Qlik-based repor=ng environments, including report refreshes, dashboard availability,

data model issues and user access coordina=on.

Ensure repor=ng outputs are aligned with business defini=ons, KPI logic and approved source

data.

Work with business users to resolve repor=ng issues, KPI discrepancies, data gaps and

dashboard enhancement requests.

Coordinate with BI developers and data teams to ensure =mely delivery of repor=ng changes.

7. SLA, KPI & Business-Cri=cal Data Governance

Own opera=onal SLAs for data availability, data freshness, report refresh comple=on,

campaign readiness and downstream data delivery.

Monitor and report SLA performance across batch loads, Glue jobs, Airflow DAGs, SAS jobs, BI

reports, campaign data feeds and cri=cal dashboards.

Establish opera=onal controls for: o Batch comple=on o DAG success/failure monitoring o Glue

job execu=on o Data freshness o Data completeness o Report availability o Data reconcilia=on

o Incident response o Business communica=on

Understand business-cri=cal KPIs and ensure data plaDorms support accurate and =mely KPI

repor=ng.

Drive root cause analysis for SLA breaches, recurring failures, data quality issues and delayed

business repor=ng.

Define preven=ve ac=ons and con=nuous improvement plans to reduce repeat incidents.

8. Incident, Problem & Change Management

Lead major incident response for BI/data plaDorm issues impac=ng businesscri=cal repor=ng,

campaigns, decisioning or data delivery.

Drive problem management for recurring ETL failures, Glue failures, DAG failures, data quality

issues, report delays and plaDorm instability.

Ensure proper RCA documenta=on, correc=ve ac=ons and preven=ve controls are

implemented.

Govern produc=on changes, deployment plans, rollback plans and implementa=on readiness.

Coordinate with applica=on teams, DBAs, data engineers, cloud plaDorm teams, infrastructure

teams, business users and service management teams.

Ensure opera=onal processes follow ITIL-aligned prac=ces where applicable. Internal JD

references also men=on ITIL and Agile as desirable process knowledge.

9. Data Quality, Controls & Opera=onal Assurance

Ensure opera=onal checks are in place for completeness, accuracy, =meliness and consistency

of business-cri=cal data.

Define and review reconcilia=on checks across source systems, warehouse layers, Glue

pipelines, Airflow DAGs, BI reports and downstream extracts.

Work with governance and data teams to improve lineage, metadata, business defini=ons and

data quality controls.

Iden=fy gaps in opera=onal monitoring and implement proac=ve alerts, dashboards and

excep=on repor=ng.

Ensure cri=cal business data is validated before being consumed for repor=ng, campaign

execu=on, decisioning or regulatory/business decisions.

10. Team Management & Delivery Governance

Manage and mentor cross-func=onal BI/Data opera=ons teams across onshore, offshore and

vendor delivery models.

Allocate work across incident support, change delivery, plaDorm opera=ons, pipeline

monitoring, repor=ng support and business requests.

Ensure team members follow defined processes for documenta=on, handovers, deployments,

produc=on support and issue resolu=on.

Build domain knowledge within the team across telecom business processes, data flows, KPIs,

SLAs, plaDorms and pipeline dependencies.

Drive knowledge transi=on, succession planning and opera=onal resilience.

Review team performance against opera=onal metrics, SLA adherence, issue resolu=on quality

and stakeholder sa=sfac=on.

Required Technical Skills / Mandatory Skills / Skill Area Required Capability

Data

Warehousing Strong understanding of enterprise data warehouse concepts, ETL/ELT, data marts,

dimensional modelling, facts, dimensions, aggrega=ons and repor=ng layers

Teradata Strong working knowledge of Teradata database opera=ons, SQL, performance tuning, load

processes and produc=on support

AWS RedshiJ Experience managing/suppor=ng RedshiJ workloads, data loads, query performance,

workload monitoring and cloud data warehouse opera=ons

AWS Glue Experience with Glue jobs, crawlers, ETL/ELT processing, scheduling, monitoring, job failure

handling and integra=on with cloud data plaDorms

Apache Airflow Experience managing Airflow orchestra=on, DAG monitoring, task dependencies,

retries, SLA misses, opera=onal alerts and failed pipeline recovery

DAG

Management Strong understanding of DAG design principles,

upstream/downstream dependencies, restartability, scheduling, opera=onal ownership and

dependency mapping

SAS DI Experience managing/suppor=ng SAS Data Integra=on jobs, ETL flows, batch schedules and

opera=onal failures

SAS CI Understanding of campaign management processes, campaign data prepara=on, segmenta=on,

eligibility and marke=ng opera=ons

SAS RTDM Understanding of real-=me decisioning, interac=on decision logic and opera=onal support

of decisioning plaDorms

Qlik Experience suppor=ng Qlik dashboards/reports, refresh cycles, data models and business

repor=ng issues

SQL Strong SQL skills for data analysis, troubleshoo=ng, reconcilia=on and performance inves=ga=on

Produc=on Support Strong experience in incident, problem, change, release, deployment and SLA

management

Stakeholder Management Ability to communicate clearly with senior business and technical

stakeholders

Internal references explicitly men=on Teradata RDBMS, SAS DI, RTDM, Qlik and related BI technologies

in telecom/BI environments.

Desirable Skills

Telecom domain experience across BSS, OSS, CRM, billing, charging, campaign, customer,

product, revenue or network datasets.

Experience in hybrid data environments involving legacy BI plaDorms and cloudna=ve data

plaDorms.

Experience with AWS S3, Lambda, IAM, CloudWatch, Step Func=ons or other AWS ecosystem

services.

Experience with pipeline observability, opera=onal dashboards, aler=ng, automa=on and

proac=ve monitoring.

Experience with data governance, metadata management, lineage, data quality and

opera=onal controls.

Experience in cloud migra=on or moderniza=on from legacy DWH plaDorms to cloud

plaDorms.

Familiarity with ITIL, Agile, DevOps, CI/CD and release governance processes.

Understanding of data privacy, customer data handling and opera=onal risk controls.

Telecom Domain Knowledge

The ideal candidate should have good understanding of telecom business data and opera=onal

processes, including:

Customer lifecycle data

Billing and revenue data

Product and plan data

Recharge/payment data

CDR/usage data

Network and service data

Campaign and offer data

Customer segmenta=on and eligibility data

KPI repor=ng for business, opera=ons, marke=ng and execu=ve teams

Telecom exposure is desirable because the role requires understanding how businesscri=cal

data supports daily opera=onal decisions, customer campaigns, revenue repor=ng, service

performance and execu=ve KPI dashboards. Exis=ng internal references describe telecom

environments involving BSS/OSS, Siebel, SAS, Teradata, RTDM and Qlik applica=ons.

Business & Leadership Competencies

The candidate should demonstrate:

Strong business-facing communica=on skills.

Ability to explain technical data/plaDorm issues in simple business language.

Strong ownership mindset for produc=on stability and business outcomes.

Ability to manage high-pressure incidents and cri=cal escala=ons.

Strong stakeholder management across business, IT, vendors and opera=ons teams.

Strong analy=cal and problem-solving ability.

Ability to lead teams across legacy BI, SAS, cloud data plaDorms and orchestra=on

technologies.

Good understanding of cri=cal KPIs, SLA commitments and data-driven business processes.

Strong documenta=on, governance and process discipline.

Ability to drive automa=on, monitoring improvements and opera=onal efficiency.

Qualifica=ons

Bachelor's degree in Computer Science, Engineering, Informa=on Technology, Data Analy=cs

or equivalent discipline.

10+ years of experience in BI, Data Warehousing, Data Opera=ons, Data PlaDorm Management

or Cloud Data Opera=ons.

Prior experience in telecom, banking, u=li=es or large enterprise data environments is

preferred.

Experience managing produc=on support teams or BI/Data opera=ons teams is strongly

preferred.

Main Du=es / Responsibili=es – HR Format

The BI / Data Opera=ons Domain Manager will be responsible for:

Managing day-to-day opera=ons of BI, Data Warehouse, Cloud Data and Analy=cs plaDorms.

Ensuring stable execu=on of Teradata loads, SAS flows, AWS Glue jobs, Airflow DAGs, Qlik

refreshes, reports and campaign data processes.

Managing opera=onal support ac=vi=es across Teradata, SAS DI, SAS CI, SAS RTDM, AWS

RedshiJ, AWS Glue, Airflow and Qlik.

Monitoring DAG execu=on, Glue job failures, batch delays, ETL failures, report refresh issues

and business-cri=cal data delivery risks.

Ensuring business-cri=cal reports, dashboards, extracts and data feeds are delivered within

agreed SLA =melines.

Monitoring business-cri=cal KPIs, data freshness, data completeness and data availability.

Leading incident resolu=on, root cause analysis and preven=ve ac=on planning for produc=on

issues.

Coordina=ng with business stakeholders for KPI issues, report delays, campaign data readiness

and produc=on escala=ons.

Managing release, change and deployment governance for BI/Data plaDorm changes.

Leading onshore/offshore teams and ensuring opera=onal con=nuity across support windows.

Driving con=nuous improvement through automa=on, proac=ve monitoring, orchestra=on

improvements and process op=miza=on.

Suppor=ng data quality, reconcilia=on, lineage and governance ini=a=ves.

Ensuring compliance with opera=onal processes, documenta=on standards and enterprise

delivery prac=ces.