Senior Data Engineer

carlsys technologies pte. ltd.; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

carlsys technologies pte. ltd. is seeking a data engineering professional to drive democratisation of data and analytics across the enterprise.

You will build and maintain data pipelines, collaborate with product engineering and data science teams, and deliver scalable data workloads and dashboards for business outcomes. The role requires hands-on experience with cloud-based data platforms, Terraform Cloud, Git, and AWS analytics services.

Qualifications

• 5+ years of hands-on experience in cloud-based data engineering or related roles.
• Experience with Terraform Cloud.
• Experience with Git for version control and release management.
• Experience with AWS data services and BI tools.
• Strong communication with stakeholders.

Responsibilities

• Democratise data and data products across the business.
• Drive analytics and dashboards to track key metrics.
• Collaborate with product engineering, data science and business teams.
• Build scalable data workloads in cloud and open-source tech.
• Work with media industry data practitioners to deliver innovative data products.
• Design data models and schemas for data lake, warehouse and marts.
• Implement scalable data pipelines and governance.
• Apply agile methodologies such as Scrum.
• Utilise Python, Spark and SQL for data processing.

Skills

Data Engineering

Business Analysis

Solution Architecture

Python

Spark

SQL

Tools

AWS EMR

AWS Glue

AWS Lambda

Step Functions

Athena

Kinesis

QuickSight

Tableau

Presto

Job description

Responsibilities:

• Support the business’s goal of democratisation of data and data products.


• Drive audience and behavioural analytics, as well as key business metrics with associated dashboard and reporting.


• Collaborate in partnership with diverse teams across organization such as product engineering, data science and business stakeholder teams to successfully deliver business outcomes.


• Work with a mix of cloud infrastructure and open-source technologies to build, scale, and maintain data workloads.


• Work with media industry data practitioners in domains across sales, marketing and advertising, engineering, corporate and organization publications to deliver innovative and game changing data products and use cases.


• Work to design, build and implement data workloads across both high and low volume and velocity of data to support business use cases.


• Implement cloud-based scalable and reliable data pipelines at significant scale.


• Implement reliable and redundant data workloads to provide accurate, easy-to-use and timely data to deliver positive business outcomes.


• Build and maintain streaming and batch data pipelines.


• Build and maintain transactional and analytical data schemas for data lake, data warehouse and data marts.


• Implement Data Analytics and Business Intelligence frameworks to support Enterprise Data needs.


• Adhere to Data Governance policies and implementation from collection to storage and activation of a broad range of data products.


• Utilise data-related languages and frameworks such as Python, Spark, SQL, Hudi, Iceberg.


• Propose Solutions for Data Pipelines, Data Schema and/or Business Intelligence Dashboards and Reports.


• Adhere and have practised Agile Methodology such as Scrum.


• Implement adhering to Master Data Management Best Practices and Principles.


• Understand and Design Data Models following BI Best Practices such as Dimensional Modelling.

Requirements:

• At least 5 years of relevant hands-on experience in cloud-based data engineering, business analyst, or solution architect roles.


• Experience in data-related infrastructure deployments using Terraform Cloud.


• Experience in using Git for version and release management with knowledge in branching strategies.


• Experience in AWS Data and Analytics services such as EMR, Glue, Lambda, Step Functions, Athena, Kinesis, or QuickSight.


• Implementation Experience in Business Intelligence Platforms and Tools such as Tableau, QuickSight.


• Experience in utilising query engines such as Presto on Data Lakes, Data Warehouses and Data Marts.


• Good communication skills for Data and Analytics concepts and methodologies and how they are relevant to your stakeholders.