Data Engineer

UniqueHire; Sydney; On-site; AUD 150,000 - 190,000; Full time

Job summary

UniqueHire is seeking a Senior AWS Data Engineer to design, build, and support scalable data pipelines and curated datasets on the AWS platform. The role involves ingesting, transforming, and serving data for reporting and analytics, with hands-on SQL/Python and strong AWS-native services experience.

You will collaborate with cross-functional teams, implement DataOps practices, and contribute to data quality, monitoring, and operational runbooks while supporting production deployments.

Qualifications

• 8–10 years’ experience as a Data Engineer.
• Advanced SQL skills.
• Hands-on experience with Teradata and Siebel CRM data sets.
• Experience delivering data pipelines in large-scale enterprise environments.
• Strong AWS data services experience (S3, Glue, Redshift, Athena, EMR) and dbt.
• Python and PySpark data transformation expertise.
• Experience with Airflow or similar workflow tools.
• Knowledge of data warehousing concepts and dimensional modelling.

Responsibilities

• Design, develop, and maintain end-to-end data pipelines on AWS Data Platform.
• Build and manage ETL/ELT workflows using AWS services and dbt.
• Ingest, transform, and curate data for reporting, analytics, and downstream apps.
• Develop transformation logic in SQL and Python/PySpark.
• Implement data quality checks, monitoring, and alerting.
• Collaborate with analysts/data scientists to model datasets for analytics.
• Contribute to DataOps/DevOps practices, including CI/CD and runbooks.
• Produce and maintain technical documentation of data flows and job schedules.
• Support production deployments and operations.

Skills

Advanced SQL

Python

PySpark

AWS

Data warehousing

ETL/ELT

Airflow

Teradata

Siebel CRM data

Communication

Tools

dbt

Airflow

Job description

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 Responsibilities

• Design, develop, and maintain end-to-end data pipelines (batch and near real-time) on AWS Data Platform
• Build and manage ETL/ELT workflows using AWS services (e.g., AWS Glue, S3, Redshift, Athena, EMR), dbt and orchestration tools such as Airflow
• Implement data ingestion patterns from diverse sources (databases, APIs, files, event streams) into lake/warehouse layers such as raw, cleansed, and curated data layers
• Develop transformation logic using SQL and Python/PySpark for cleansing, enrichment, and standardisation
• Implement robust data quality checks, reconciliation controls, and monitoring/alerting for failures and anomalies
• Collaborate 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 scheduling
• Support production deployments and operations

Required Skills & Experience

• 8–10 years’ experience as a Data Engineer
• Advanced SQL skills
• Hands-on experience working with Teradata and Siebel CRM data sets
• Experience delivering data pipelines in a large-scale enterprise data platform environment
• Strong hands-on AWS experience with common data services such as : Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR and dbt
• Strong programming capability in Python and strong 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 Airflow
• Solid 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 deliverables
• Telco Industry Experience is highly desirable