Data Platform Engineer

EatClub

. Build and operate ingestion into the bronze layer, including source integrations, CDC feeds and third-party APIs .

Posted 9/30/2026full-timeSydney • AustraliaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating data ingestion pipelines, ensuring data quality and observability, and optimizing performance on cloud data platforms. Proficient in orchestration workflows and CI/CD practices, with a strong focus on data integrity and security.

Highest-signal resume keywords

SQL OptimizationPython ProgrammingData Pipeline DevelopmentOrchestration Tools ExperienceData Quality Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData PipelineCI/CDOrchestrationData QualitySchema EvolutionCost OptimizationPerformance TuningStreaming

Tools & Technologies

DatabricksAirflowDagsterDbt CoreAWSClaude CodeDebeziumDelta Live Tables

Industry Keywords

Data IngestionCDCData IntegrityData SecurityObservabilitySelf-Serve PlatformAI Tooling

Tech Stack

Tools & technologies

AirflowAWSCloudPythonSparkSQL

About the role

Key responsibilities & impact

Build and operate ingestion into the bronze layer, including source integrations, CDC feeds and third-party APIs
Handle schema evolution, backfills and replay
Own orchestration workflows, including scheduling, dependencies, retries, alerting and dataset SLAs
Harden CI/CD through trunk-based development, pull-request checks, deployment-gating tests and clean environment promotion
Govern the platform through grants, lineage, tagging, row-level and column-level security, and safe external data sharing
Own cost and performance by right-sizing warehouses and clusters and tuning partitioning, clustering and incremental strategies
Build data quality and observability, including freshness, volume and schema checks, break alerting and root-cause analysis
Make the platform self-serve for analysts and data scientists
Collaborate with analytics and data science teams whose models and dashboards depend on the platform
Leverage AI tooling to expedite development, testing, migration and review

Requirements

What you’ll need

Solid experience writing and optimising SQL for commercial-scale products
Strong Python skills
Hands-on experience building and operating production data pipelines on a cloud data platform
Experience with orchestration and scheduling such as Databricks Workflows, Airflow, Dagster or similar
Experience handling failed overnight jobs
Experience working with internal APIs and third-party tools to ingest data efficiently while maintaining strict data integrity
Strong grasp of software engineering best practices including Git, CI/CD, trunk-based development and testing
Familiarity with an AI-first working style, including Claude Code, agentic workflows and AI in the daily development loop
Experience using Databricks and dbt Core is advantageous
Familiarity with AWS is advantageous
Experience tuning cost and performance on Spark or Databricks, including partitioning, liquid clustering and warehouse sizing, is advantageous
Streaming or CDC experience, including Structured Streaming, Debezium or Delta Live Tables, is advantageous
Experience implementing data quality, security and documentation best practices is advantageous
Experience with AI and LLM experiments is advantageous

Benefits

Comp & perks

Staff discounts and dining vouchers to enjoy through EatClub
Optional $5 voucher for first-time users who try EatClub using code "ECAPPLY5"; voluntary and does not impact the application or interview process
AI-first culture with Claude Code via Anthropic Enterprise, agentic and async workflows
Opportunity to work on a Databricks lakehouse platform
Small, high-leverage team
Fast shipping and weekly feedback