Data Engineer – ETL, SQL & Data Warehouse

Spait Infotech; Australia; On-site; AUD 90,000 - 150,000; Full time

Job summary

Spait Infotech in Australia is seeking a data engineer to develop and maintain ETL/ELT pipelines, and to extract, transform and load data from multiple sources. You will write and optimize SQL, use Python for data processing, and design databases and data warehouses while ensuring data quality.

Freshers welcome; strong interest in data engineering encouraged. The role offers opportunities to collaborate with data analysts and cross-functional teams in a dynamic environment.

Qualifications

• Strong knowledge of SQL.
• Basic to intermediate knowledge of Python.
• Understanding of ETL/ELT concepts.
• Knowledge of databases such as MySQL, PostgreSQL, or SQL Server.
• Understanding of data warehousing concepts.
• Knowledge of cloud platforms (AWS, Azure, or GCP) is an advantage.
• Good problem-solving and communication skills.
• Freshers are welcome to apply. Candidates with a strong interest in Data Engineering are encouraged to apply.

Responsibilities

• Develop and maintain ETL/ELT data pipelines.
• Extract, transform, and load data from multiple sources.
• Write and optimize SQL queries.
• Work with Python for data processing and automation.
• Design and maintain databases and data warehouses.
• Ensure data quality, accuracy, and consistency.
• Collaborate with data analysts and other technical teams.

Skills

SQL

Python

ETL/ELT concepts

Data warehousing concepts

Data quality

Problem solving & communication

Tools

MySQL

PostgreSQL

SQL Server

AWS

Azure

GCP

Job description

Spait Infotech in Australia is seeking a data engineer to develop and maintain ETL/ELT pipelines, and to extract, transform and load data from multiple sources. You will write and optimize SQL, use Python for data processing, and design databases and data warehouses while ensuring data quality.

Freshers welcome; strong interest in data engineering encouraged. The role offers opportunities to collaborate with data analysts and cross-functional teams in a dynamic environment.