Job Description

Join to apply for the GCP BigData Engineering role at XPT Software

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Sydney, New South Wales, Australia

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Top 3 Must‐Have Skillsets

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- GCP BigData Engineering (BigQuery + Dataform + Pub/Sub)
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- Expert in designing and optimising BigQuery schemas, partitioning/clustering, cost/performance tuning, query optimisation, and policy tag integration.
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- Building streaming and batch pipelines using Apache Beam/Dataflow and Pub/Sub with exactly‐once semantics, backpressure handling, and replay strategies.
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- Strong experience with Dataform (or similar) for SQL‐based transformations, dependency graphs, unit tests, and multi‐environment deployments.
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- Production‐grade Python for ETL/ELT, distributed processing, robust error handling, and testable modular design.
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- Designing resilient Airflow DAGs on Cloud Composer: dependency management, retries, SLAs, sensors, service accounts, and secrets.
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- Monitoring, alerting, and Cloud Logging/Stackdriver integration for end‐to‐end pipeline observability.
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- Data Security & Governance on GCP
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- Hands‐on with Dataplex (asset management, data quality, lineage), BigQuery policy tags, Cloud IAM (least privilege, fine‐grained access), KMS (key rotation, envelope encryption), and audit trails via Cloud Logging.
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- Practical experience implementing PII controls (data masking, tokenisation, attribute‐based access control) and privacy‐by‐design in pipelines.
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Additional Expertise

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- Cloud Run & APIs: Building stateless microservices for data access/serving layers, implementing REST/gRPC endpoints, authentication/authorisation, rate limiting.
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- Data Modelling: Telecom‐centric event models (e.g., CDRs, network telemetry, session/flow data), star/snowflake schemas,



and lakehouse best practices.
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- Performance Engineering: BigQuery slot management, materialised views, BI Engine, partition pruning, cache strategies.
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- Secure Source Manager (CI/CD): Pipeline‐as‐code, automated tests, artifact versioning, setting promotion, canary releases, and GitOps patterns.
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- Data Quality & Testing: Great Expectations/Deequ‐like checks, schema contracts, anomaly detection, and automated data validations in CI/CD.
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- Streaming Patterns: Exactly‐once delivery, idempotent sinks, watermarking, late data handling, windowing strategies.
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- Observability & SRE Practices: Metrics, logs, traces, runbooks, SLIs/SLOs for data platforms, major incident response to support DevOps.
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- Cost Governance: BigQuery cost controls, slot commitments/reservations, workload management, storage lifecycle policies.
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- Domain Knowledge (Mobile Networks): Familiarity with 3G/4G/5G network data, OSS/BSS integrations, network KPIs, and typical analytics use cases.
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Experience Level

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- 7+ years total in data engineering; 4+ years on GCP with production systems
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- Evidence of impact:
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- • Led end‐to‐end delivery of large‐scale pipelines (batch + streaming) with strict PII governance.
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- • Owned performance/cost optimisation initiatives in BigQuery/Dataflow at scale.
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- • Implemented CI/CD for data workflows (Secure Source Manager) including automated tests and environment promotion.
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- • Drove operational excellence (SLAs, incident management, RTO/RPO awareness, DR patterns).
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- Soft skills: Technical leadership, code reviews, mentoring, clear documentation, cross‐functional collaboration with Network/Analytics teams, and a bias for automation & reliability.
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📌 GCP BigData Engineering (New South Wales)
🏢 XPT Software
📍 New South Wales