The Senior AWS Data Engineer is responsible to design, build, and support scalable data pipelines and curated datasets on AWS.He/She will work with cross functional teams to ingest, transform, and serve data for reporting, analytics, and downstream applications.The ideal candidate is hands on, strong in SQL/Python, and experienced with AWS native data services and modern data engineering practices.Key ResponsibilitiesDesign, develop, and maintain end to end data pipelines (batch and near real time) on AWS Data PlatformBuild and manage ETL/ELT workflows using AWS services (e.g., AWS Glue, S3, Redshift, Athena, EMR), dbt and orchestration tools such as AirflowImplement data ingestion patterns from diverse sources (databases, APIs, files, event streams) into lake/warehouse layers such as raw, cleansed, and curated data layersDevelop transformation logic using SQL and Python/PySpark for cleansing, enrichment, and standardisationImplement robust data quality checks, reconciliation controls, and monitoring/alerting for failures and anomaliesCollaborate with data analysts/data scientists to model datasets for analytics and machine learning consumption.Contribute to DataOps/DevOps practices: version control, CI/CD, automated testing, release management, and operational support.Produce and maintain technical documentation (data flows, mappings,



job schedules, runbooks, and operational procedures)Optimise Data Pipeline performance and Support workflow orchestration and schedulingSupport production deployments and operationsRequired Skills & Experience7 experience as a Data EngineerAdvanced SQL skillsHands on experience working with Teradata and Siebel CRM data setsExperience delivering data pipelines in a large scale enterprise data platform environmentStrong hands on AWS experience with common data services such as : Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR and dbtStrong programming capability in Python and robust data transformation experience using PySpark (preferred) and/or Spark.Advanced SQL skills (query optimisation, complex joins, window functions, performance tuning)Experience with workflow orchestration tools such as AirflowSolid understanding of data warehousing concepts (dimensional modelling, partitioning, incremental loads, CDC concepts).
Experience implementing monitoring, logging, alerting, and operational support processes.Strong communication skills and ability to work with stakeholders to translate requirements into data deliverablesTelco Industry Experience is highly desirable
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📌 Sr. Data Engineer (Aws + Telecom) (New South Wales)
🏢 CareCone Group
📍 New South Wales