Data engineer (Azure)

Flintex Consulting Pte Ltd; Singapore; On-site; SGD 45,000 - 50,000; Full time

Job summary

Flintex Consulting Pte Ltd is seeking a data engineer (Azure) to design and implement PySpark data pipelines, establish data connections and manage data across storage and data warehouse environments in Singapore. The role emphasizes Azure Synapse, Power BI reporting, and DevOps practices, with on-site hours 8:30am–6pm, Monday to Friday, and a focus on collaboration and reliable data delivery.

You will work with on-prem and cloud data sources, build scalable pipelines, ensure data quality,

Qualifications

• Bachelor’s degree in Computer Science or Engineering with 2 years of experience in Azure Data engineering, Python, PySpark or Big Data development.
• Sound knowledge of Azure Synapse analytics for pipelines, orchestration, set up.
• 1-2 years experience in Visualization design and development with Power BI and knowledge on row-level security.
• Sound experience in SQL, Datawarehouse, data marts, data ingestion with PySpark and Python.

Responsibilities

• Design, review and development of PySpark scripts. Testing, troubleshooting of data pipelines, orchestration.
• Designing and developing reports and dashboards in PowerBI, setting up access control with row level security DAX query experience.
• Establishing connections to source data systems such as on-prem databases, IoT devices, APIs.
• Managing the collected data in storage/data-base solutions e.g. file systems, SQL servers, Big Data platforms such as Hadoop, HANA, etc.
• Design, development of relevant data pipelines using PySpark, copy data activities for batch ingestion.
• Performing data integration e.g. using database table joins, or other mechanisms at an appropriate level.
• Deployment of pipeline artifacts from one environment to the other using Azure Devops.

Skills

Azure Data Engineering

Python

Pyspark

Big Data

SQL

Power BI

ETL pipelines

Azure Synapse

DevOps

Education

Bachelor’s Degree in Computer Science or Engineering

Tools

Azure DevOps

Azure Synapse

SQL Server

Hadoop

Data Factory

Power BI

Job description

Job Information

Work Experience 1-3 years

Technology

SGD 4000 -SGD 4500

City Singapore

State/Province Central Singapore

079903

Job Description

Data engineer (Azure) – Synapse and Pyspark, Python, Datawarehouse and Azure Data Explorer, Azure Devops

Job Scope

• Design, review and development of Pyspark scripts. Testing, troubleshooting of data pipelines, orchestration.
• Designing and developing reports and dashboards in PowerBI,setting up access control with row level security DAX query experience.
• Establishing connections to source data systems such as on-prem databases, IOT devices, APIs.
• Managing the collected data in appropriate storage/data-base solutions e.g. file systems, SQL servers, Big Data platforms such as Hadoop, HANA, etc. as required by the specific project requirements.
• Design, development of relevant data pipelines using pyspark, copy data activities for batch ingestion.
• Performing data integration e.g. using database table joins, or other mechanisms at an appropriate level as required by the analysis requirements of the project.
• Deployment of pipeline artifacts from one environment to the other using Azure Devops.

Skills & Experience

• Bachelor’s Degree in Computer Science or Engineering with 2 years of experience in Azure Data engineering, Python, Pyspark or Big Data development.
• Sound Knowledge of Azure Synapse analytics for pipelines, orchestration, set up.
• 1-2 experience in Visualization design and development with Power BI. Knowledge on row-level security, access control.
• Sound experience in SQL, Datawarehouse, data marts, data ingestion with Pyspark and Python.
• Expertise in developing and maintaining ETL processing pipelines in cloud-based platforms such as AWS, Azure, etc. (Azure Synapse or data factory preferred)
• Team player with good interpersonal, communication, and problem-solving skills.
• Preferred to have Devops expertise.

Working hours

8:30am to 6pm (Monday to Friday) onsite, no hybrid option.