👨🏻‍💻 postech.work

Data Engineer – Azure & Databricks

N2S.Global • 🌐 In Person

In Person Posted 3 days ago

Job Description

Job Title:

Data Engineer – Azure \& Data bricks

Location:

Sydney/Melbourne

About the Role

We are looking for an experienced

Data Engineer

with strong expertise in

Microsoft Azure

and

Databricks

to design, develop, and optimize data solutions. You will be responsible for building scalable data pipelines, managing big data environments, and enabling advanced analytics for business insights.

Key Responsibilities

Design and implement

data pipelines

using

Azure Data Factory

,

Databricks

, and related services.

Develop and optimize

ETL/ELT workflows

for structured and unstructured data.

Build and maintain

data lakes and data warehouses

on Azure.

Implement

data governance, security, and compliance

standards.

Collaborate with data scientists and analysts to deliver

high-quality datasets

for analytics and machine learning.

Monitor and troubleshoot

data workflows

for performance and reliability.

Work with

Spark

and

PySpark

for big data processing in Databricks.

Integrate data from multiple sources including

APIs, streaming data, and on-prem systems

.

Required Skills \& Qualifications

Bachelor’s degree in

Computer Science, Engineering, or related field

.

Hands-on experience with

Azure services

:

Azure Data Factory

,

Azure Synapse Analytics

,

Azure Data Lake Storage

,

Azure SQL Database

.

Strong experience with

Databricks

,

Apache Spark

, and

PySpark

.

Proficiency in

Python

and

SQL

for data engineering tasks.

Knowledge of

data modeling

,

data governance

, and

security best practices

.

Familiarity with

CI/CD pipelines

and

DevOps practices

for data solutions.

Preferred Qualifications

Experience with

real-time data streaming

(Azure Event Hub, Kafka).

Knowledge of

Delta Lake architecture

and

Lakehouse concepts

.

Familiarity with

Power BI

or other visualization tools.

Understanding of

machine learning workflows

in Databricks.

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