Remote Data Engineer: Scalable Pipelines & Analytics

Huzzle

Philippines

Remote

PHP 5,678,000 - 7,571,000

Full time

3 days ago

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Benefits offered by this job

Competitive compensation

Fully remote work

Career development

Long-term potential

Ongoing learning

Collaborative environment

Modern tech stack

Job summary

Huzzle is seeking a Data Engineer to design, develop, and maintain scalable data pipelines and infrastructure for diverse client projects. You will collaborate with data analysts, data scientists, software engineers, and business stakeholders to ensure data is reliable, accessible, and of high quality across the organisation.

This is a great opportunity for professionals who enjoy tackling complex data challenges and building robust systems that power business intelligence, analytics, and

Qualifications

2+ years of experience in data engineering, data warehousing, or a similar field.
Strong SQL skills and a solid understanding of database management.
Proficiency in Python, Java, Scala, or other relevant programming languages.
Practical experience with ETL/ELT tools and building data pipelines.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Hands-on experience with modern data warehouse solutions such as Snowflake, Redshift, BigQuery, or Databricks.
Knowledge of workflow orchestration tools such as Airflow or Prefect.
Understanding of data modelling, governance, and data quality best practices.
Experience handling large datasets and working with distributed systems is an advantage.
Strong analytical thinking, problem-solving, and communication abilities.
Comfortable working independently while collaborating with a remote team.

Responsibilities

Design, build, and maintain scalable ETL and ELT data pipelines.
Develop and optimize data architectures, databases, and data warehouses.
Integrate data from various sources, APIs, and third-party platforms.
Maintain data quality, accuracy, consistency, reliability, and security.
Monitor, troubleshoot, and improve data pipelines and workflows.
Work closely with analytics, engineering, and business teams to identify and meet data requirements.
Establish data governance standards and best practices for data management.
Improve data storage, processing speeds, and query performance.
Support business intelligence, reporting, and analytics projects.
Maintain documentation of data models, workflows, and technical processes.

Skills

SQL

Python

Java

Scala

ETL/ELT pipelines

AWS

Azure

Google Cloud Platform

Snowflake

Redshift

BigQuery

Databricks

Airflow

Prefect

Data modelling

Data governance

Data quality

Distributed systems

Analytical thinking

Communication

Tools