Data Engineer

Encora Inc.; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Encora Inc. in Malaysia is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines and ETL/ELT workflows using modern data platforms.

The ideal candidate has hands-on experience with Snowflake or Databricks, Azure cloud services, SQL tuning, and Python/Scala. You will collaborate with Data Analytics, Data Science, Product, and Engineering teams to meet data consumption needs.

Qualifications

• 7-8+ years hands-on experience as a Data Engineer.
• Deep experience with Snowflake and/or Databricks.
• Hands-on Azure Cloud experience with multiple services.
• Expertise in SQL and performance tuning for large datasets.
• Experience developing ETL/ELT pipelines.
• Proficiency in Python or Scala.
• Experience with data modeling (star schema, dimensional).
• CI/CD for data pipelines and Git version control.
• Exposure to data governance and data quality frameworks.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows.
• Develop and optimize data lake and warehouse solutions using Snowflake/Databricks.
• Implement ingestion, transformation, and processing frameworks for structured and unstructured data.
• Collaborate with cross-functional teams to support data consumption needs.
• Build reusable and modular data pipeline components aligned with best practices.
• Implement data quality validation, reconciliation, and monitoring controls.
• Optimize performance for data storage, compute, and query execution.
• Ensure adherence to data governance, security standards, and compliance requirements.
• Participate in solution architecture discussions and contribute to design decisions.

Skills

SQL

Performance tuning

ETL/ELT pipelines

Python

Scala

Data modeling

CI/CD for data pipelines

Data governance

Tools

Snowflake

Databricks

Azure Data Factory

Azure Synapse

Azure Key Vault

Azure Functions

Azure DevOps

Git

Job description

About the Role

We are looking for a Senior Data Engineer with strong experience in modern data platforms and cloud-based architectures. The ideal candidate has deep hands‑on experience with Snowflake or Databricks, has built scalable data pipelines, and is proficient in Azure cloud services.

About the Role

We are looking for a Senior Data Engineer with strong experience in modern data platforms and cloud-based architectures. The ideal candidate has deep hands‑on experience with Snowflake or Databricks, has built scalable data pipelines, and is proficient in Azure cloud services.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows.
• Develop and optimize data lake and data warehouse solutions using Snowflake and/or Databricks.
• Implement data ingestion, transformation, and processing frameworks for structured and unstructured datasets.
• Work closely with cross‑functional teams (Data Analytics, Data Science, Product, Engineering) to support data consumption needs.
• Build reusable and modular data pipeline components aligned with best practices.
• Implement data quality validation, reconciliation, and monitoring controls.
• Optimize performance for data storage, compute, and query execution.
• Ensure adherence to data governance, security standards, and compliance requirements.
• Participate in solution architecture discussions and contribute to technical design decisions.

Required Skills & Experience

• 7-8+ years of hands‑on experience as a Data Engineer.
• Strong experience in Snowflake and/or Databricks (any one is fine, both preferred).
• Hands‑on experience on Azure Cloud (e.g., Azure Data Factory, ADLS, Azure Synapse, Azure Key Vault, Azure Functions, Azure DevOps).
• Expertise in SQL and performance tuning for large datasets.
• Experience developing ETL/ELT pipelines using modern data frameworks.
• Proficiency with scripting languages such as Python or Scala.
• Experience with data modeling techniques (star schema, normalized models, dimensional modeling).
• Experience with CI/CD for data pipelines and version control (Git).
• Exposure to data governance, metadata management, and data quality frameworks.