Data Engineer (Matillion)
Overview
We are seeking a
Data Engineer
with strong experience in
Matillion
and hands-on expertise in cloud-based data platforms. This role will be responsible for developing, maintaining, and enhancing a modern analytics ecosystem, ensuring that data pipelines are reliable, scalable, and aligned with business needs.
The ideal candidate has solid ETL/ELT knowledge, advanced SQL skills, and the ability to translate analytical requirements into efficient data models across Bronze, Silver, and Gold layers.
Responsibilities
Design, build, and maintain ETL/ELT pipelines
using Matillion ETL within a cloud analytics environment.
Develop
scalable and efficient data transformation workflows
, following best data engineering practices.
Integrate data from multiple internal and external sources into cloud data platforms.
Optimize ingestion and transformation processes for
performance, reliability, and cost efficiency
.
Ensure robust
data quality, lineage, and governance
across all pipelines.
Collaborate with Data Engineers, Analysts, and business stakeholders to translate analytical needs into well-structured, high-performing data models.
Build and maintain SQL models, views, and tables across Bronze, Silver, and Gold layers.
Support historical data loads and implement changes or extensions to existing pipelines based on evolving requirements.
Work with
CI/CD pipelines
, promoting changes through DEV, QA, and PROD environments.
Monitor and troubleshoot Matillion jobs to ensure high availability and minimal disruption.
Participate in architecture discussions, solution design, and data modeling decisions.
Contribute to continuous improvement efforts in automation, documentation, and engineering standards.
Required Skills & Experience
Hands-on experience with
Matillion ETL
or Matillion Data Loader.
Strong
SQL
skills, including complex queries, performance optimization, and troubleshooting.
Experience with cloud data warehouses such as
Snowflake
(preferred), Redshift, BigQuery, or Azure Synapse.
Familiarity with cloud platforms (AWS, Azure, or GCP), ideally AWS.
Solid understanding of
ETL/ELT concepts
, orchestration, and data integration best practices.
Experience working with structured and semi-structured data formats (CSV, JSON, Parquet, etc.).
Knowledge of
CI/CD principles
and version control (Git).
Strong analytical thinking and debugging skills.
Nice to Have
Experience with orchestration tools such as
Airflow, dbt, Prefect, or Dagster
.
Python skills for automation or custom transformation logic.
Understanding of
data modeling
(dimensional modeling, star schema).
Experience with
API integrations
or event-driven pipelines.
Familiarity with
Terraform
or other Infrastructure-as-Code tools.
Exposure to
DataOps
or
MLOps
environments.
Soft Skills
Strong communication and documentation abilities.
Ability to work effectively with technical and non-technical stakeholders.
Proactive attitude and strong sense of ownership.
Comfortable working in
Agile/Scrum
environments.