BI Data Operations Domain

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

Role Summary:

• We are looking for an experienced BI / Data Operaons Domain Manager to lead and manage enterprise-scale BI data warehouse campaign decisioning and data operaons 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 orchestraon Qlik and related BI/data ecosystem components.
• The candidate will be responsible for ensuring the stability reliability availability data freshness orchestraon health SLA adherence and operaonal governance of businesscrical data plaDorms. The role requires strong business-facing capability to work with stakeholders across technology analycs campaign reporng and operaons teams.
• The role is especially suited for a senior data operaons 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 orchestraon.
• Telecom domain experience is highly desirable especially with exposure to BSS/OSS CRM billing campaign management customer analycs CDR network revenue product and customer data. Exisng internal references menon Teradata SAS RTDM and Qlik usage in telecom BI/data environments.
• Key Responsibilities

1. BI & Data Operaons Leadership

Lead end-to-end operaons for BI data warehouse analycs campaign and reporng

plaDorms.

Manage daily weekly and monthly operaonal cycles across ETL ELT batch near-real-me

reporng campaign and decisioning workloads.

Ensure producon stability across ingeson pipelines transformaon jobs data marts

dashboards regulatory extracts and downstream data feeds.

Own operaonal readiness for new releases source changes data model changes plaDorm

upgrades migraon acvies and business-crical deployments.

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

data analysts cloud data engineers and operaons teams.

Drive operaonal discipline across incident problem change release deployment

monitoring and stakeholder communicaon processes.

2. Data Warehouse & BI PlaDorm Management

Manage and govern enterprise data warehouse operaons across Teradata AWS RedshiJ and

associated BI/data plaDorms.

Oversee data loads batch schedules source-to-target flows transformaon logic data marts

semanc layers and report availability.

Ensure performance scalability and availability of crical 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 modernizaon and coexistence between legacy data warehouse plaDorms and cloudbased plaDorms such as AWS RedshiJ. Exisng internal JD references menon data

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

3. AWS Glue & Cloud Data Operaons

Manage and support AWS Glue-based ETL/ELT pipelines used for ingeson transformaon

data preparaon and downstream data processing.

Oversee Glue jobs crawlers job schedules job dependencies failures retries and operaonal

monitoring.

Ensure AWS Glue pipelines are aligned with business-crical data processing windows and

reporng SLAs.

Work with data engineering teams to support pipeline opmizaon error handling

restartability dependency handling and operaonal resilience.

Monitor Glue job execuon data movement transformaon failures schema changes and

downstream data availability.

Support cloud data warehouse integraon paYerns involving AWS Glue AWS RedshiJ S3-

based data staging and downstream reporng plaDorms.

Ensure strong operaonal controls around cloud data processing including data

completeness reconciliaon logging alerng and escalaon.

4. Apache Airflow / DAG Orchestraon Management

Manage and govern Airflow-based orchestraon for business-crical 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 execuon health across ingeson transformaon data quality reporng and

extract delivery workflows.

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

failures and delayed data availability.

Review operaonal readiness of new DAGs before producon deployment.

Ensure proper naming standards documentaon alerng ownership and support model for

Airflow DAGs.

Drive improvements in orchestraon reliability including beYer dependency mapping

automated recovery proacve alerts and operaonal dashboards.

5. SAS PlaDorm Operaons SAS DI SAS CI & SAS RTDM

Manage operaonal support and delivery across the SAS ecosystem including:

SAS DI for ETL/data integraon workflows

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

decisioning and customer interacon use cases

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

schedules.

Support invesgaon and resoluon of SAS job failures campaign data issues RTDM

decisioning issues and dependency failures.

Coordinate with business teams on campaign readiness audience data availability

segmentaon accuracy and decisioning plaDorm stability.

Ensure robust controls around campaign data extracts eligibility logic customer targeng

data suppression rules and operaonal validaons.

Prior internal templates reference SAS DI SAS RTDM Teradata and related

deployment/support acvies.

6. Qlik / BI Reporng Operaons

Manage availability and reliability of dashboards reports extracts and businessfacing

analycs outputs.

Support Qlik-based reporng environments including report refreshes dashboard availability

data model issues and user access coordinaon.

Ensure reporng outputs are aligned with business definions KPI logic and approved source

data.

Work with business users to resolve reporng issues KPI discrepancies data gaps and

dashboard enhancement requests.

Coordinate with BI developers and data teams to ensure mely delivery of reporng changes.

7. SLA KPI & Business-Crical Data Governance

Own operaonal SLAs for data availability data freshness report refresh compleon

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 crical dashboards.

Establish operaonal controls for: o Batch compleon o DAG success/failure monitoring o Glue

job execuon o Data freshness o Data completeness o Report availability o Data reconciliaon

o Incident response o Business communicaon

Understand business-crical KPIs and ensure data plaDorms support accurate and mely KPI

reporng.

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

business reporng.

Define prevenve acons and connuous improvement plans to reduce repeat incidents.

8. Incident Problem & Change Management

Lead major incident response for BI/data plaDorm issues impacng businesscrical reporng

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 documentaon correcve acons and prevenve controls are

implemented.

Govern producon changes deployment plans rollback plans and implementaon readiness.

Coordinate with applicaon teams DBAs data engineers cloud plaDorm teams infrastructure

teams business users and service management teams.

Ensure operaonal processes follow ITIL-aligned pracces where applicable. Internal JD

references also menon ITIL and Agile as desirable process knowledge.

9. Data Quality Controls & Operaonal Assurance

Ensure operaonal checks are in place for completeness accuracy meliness and consistency

of business-crical data.

Define and review reconciliaon 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 definions and

data quality controls.

Idenfy gaps in operaonal monitoring and implement proacve alerts dashboards and

excepon reporng.

Ensure crical business data is validated before being consumed for reporng campaign

execuon decisioning or regulatory/business decisions.

10. Team Management & Delivery Governance

Manage and mentor cross-funconal BI/Data operaons teams across onshore offshore and

vendor delivery models.

Allocate work across incident support change delivery plaDorm operaons pipeline

monitoring reporng support and business requests.

Ensure team members follow defined processes for documentaon handovers deployments

producon support and issue resoluon.

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

SLAs plaDorms and pipeline dependencies.

Drive knowledge transion succession planning and operaonal resilience.

Review team performance against operaonal metrics SLA adherence issue resoluon quality

and stakeholder sasfacon.

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 aggregaons and reporng layers

Teradata Strong working knowledge of Teradata database operaons SQL performance tuning load

processes and producon support

AWS RedshiJ Experience managing/supporng RedshiJ workloads data loads query performance

workload monitoring and cloud data warehouse operaons

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

handling and integraon with cloud data plaDorms

Apache Airflow Experience managing Airflow orchestraon DAG monitoring task dependencies

retries SLA misses operaonal alerts and failed pipeline recovery

DAG

Management Strong understanding of DAG design principles

upstream/downstream dependencies restartability scheduling operaonal ownership and

dependency mapping

SAS DI Experience managing/supporng SAS Data Integraon jobs ETL flows batch schedules and

operaonal failures

SAS CI Understanding of campaign management processes campaign data preparaon segmentaon

eligibility and markeng operaons

SAS RTDM Understanding of real-me decisioning interacon decision logic and operaonal support

of decisioning plaDorms

Qlik Experience supporng Qlik dashboards/reports refresh cycles data models and business

reporng issues

SQL Strong SQL skills for data analysis troubleshoong reconciliaon and performance invesgaon

Producon 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 menon 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 cloudnave data

plaDorms.

Experience with AWS S3 Lambda IAM CloudWatch Step Funcons or other AWS ecosystem

services.

Experience with pipeline observability operaonal dashboards alerng automaon and

proacve monitoring.

Experience with data governance metadata management lineage data quality and

operaonal controls.

Experience in cloud migraon or modernizaon 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 operaonal risk controls.

Telecom Domain Knowledge

The ideal candidate should have good understanding of telecom business data and operaonal

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 segmentaon and eligibility data

KPI reporng for business operaons markeng and execuve teams

Telecom exposure is desirable because the role requires understanding how businesscrical

data supports daily operaonal decisions customer campaigns revenue reporng service

performance and execuve KPI dashboards. Exisng internal references describe telecom

environments involving BSS/OSS Siebel SAS Teradata RTDM and Qlik applicaons.

Business & Leadership Competencies

The candidate should demonstrate:

Strong business-facing communicaon skills.

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

Strong ownership mindset for producon stability and business outcomes.

Ability to manage high-pressure incidents and crical escalaons.

Strong stakeholder management across business IT vendors and operaons teams.

Strong analycal and problem-solving ability.

Ability to lead teams across legacy BI SAS cloud data plaDorms and orchestraon

technologies.

Good understanding of crical KPIs SLA commitments and data-driven business processes.

Strong documentaon governance and process discipline.

Ability to drive automaon monitoring improvements and operaonal efficiency.

Qualificaons

Bachelors degree in Computer Science Engineering Informaon Technology Data Analycs

or equivalent discipline.

10 years of experience in BI Data Warehousing Data Operaons Data PlaDorm Management

or Cloud Data Operaons.

Prior experience in telecom banking ulies or large enterprise data environments is

preferred.

Experience managing producon support teams or BI/Data operaons teams is strongly

preferred.

Main Dues / Responsibilies HR Format

The BI / Data Operaons Domain Manager will be responsible for:

Managing day-to-day operaons of BI Data Warehouse Cloud Data and Analycs plaDorms.

Ensuring stable execuon of Teradata loads SAS flows AWS Glue jobs Airflow DAGs Qlik

refreshes reports and campaign data processes.

Managing operaonal support acvies across Teradata SAS DI SAS CI SAS RTDM AWS

RedshiJ AWS Glue Airflow and Qlik.

Monitoring DAG execuon Glue job failures batch delays ETL failures report refresh issues

and business-crical data delivery risks.

Ensuring business-crical reports dashboards extracts and data feeds are delivered within

agreed SLA melines.

Monitoring business-crical KPIs data freshness data completeness and data availability.

Leading incident resoluon root cause analysis and prevenve acon planning for producon

issues.

Coordinang with business stakeholders for KPI issues report delays campaign data readiness

and producon escalaons.

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

Leading onshore/offshore teams and ensuring operaonal connuity across support windows.

Driving connuous improvement through automaon proacve monitoring orchestraon

improvements and process opmizaon.

Supporng data quality reconciliaon lineage and governance iniaves.

Ensuring compliance with operaonal processes documentaon standards and enterprise

delivery pracces.