Data Engineer — Build Scalable Data Pipelines

ECLARO; Philippines; On-site; PHP 600,000 - 900,000; Full time

Job summary

ECLARO is seeking a Data Engineer to support the Strategic Analytics data engineering needs across a growing portfolio of analytics projects. You will develop complex data structures and pipelines leveraging SQL, Python, and cloud-based tools to enable faster data analysis.

Join a team that collaborates with predictive modelers to improve profitability and growth, using Databricks, Snowflake, Spark, Python, and Azure Data Factory to build robust data solutions.

Qualifications

• 3+ years of Data Engineer experience or equivalent using SQL and/or Python.
• Advanced SQL knowledge with relational databases.
• Experience with cloud technologies and Python is a plus.
• Excellent communication and collaboration in fast-paced environments.

Responsibilities

• Assemble large, complex data sets with modelers to solve business problems and increase profitability.
• Manipulate and transform data using SQL and Python.
• Automate manual processes and optimize data pipelines.
• Discover and explore new data sources with curiosity.
• Create and maintain scalable data pipeline architecture.
• Document data pipelines and technical solutions clearly.
• Ensure data quality and completeness.

Skills

Advanced SQL knowledge

Relational databases

3+ years data engineering

Attention to detail

Critical thinking

Communication skills

Fast-paced collaboration

Data quality awareness

Education

BS in Computer Science / IT / Data Analytics

Tools

Azure Data Factory

Snowflake

Databricks

Python

Spark

SQL tooling

Job description

ECLARO is seeking a Data Engineer to support the Strategic Analytics data engineering needs across a growing portfolio of analytics projects. You will develop complex data structures and pipelines leveraging SQL, Python, and cloud-based tools to enable faster data analysis.

Join a team that collaborates with predictive modelers to improve profitability and growth, using Databricks, Snowflake, Spark, Python, and Azure Data Factory to build robust data solutions.