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 solid 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.

📌 Bi / Data Operations Domain (New South Wales)
🏢 The HR Ally
📍 New South Wales