Senior Data Engineer

Required Qualifications

• 5 to 8 years of experience in data engineering roles, with 3+ years of hands-on experience working with Snowflake and dbt in production environments, and demonstrable project experience with Matillion (Data Productivity Cloud or Matillion ETL

)
Technical Skill
s:◦ Cloud Data Warehouse & Transformation Stac
k:1 . Expert-level knowledge of SQL and Snowfla ke, including performance optimization, storage layers, query profiling, clustering, and cost managemen
t.2 . Experience in dbt developme nt: modular model design, macros, tests, documentation, and version control using Gi
t.3 . Hands-on experience with Matillion Data Productivity Clo ud, including Designer pipelines, orchestration jobs, transformation jobs, variables, shared jobs, and Git-based project managemen

t.
◦ Orchestration and Integrati
on:
1. Proficiency in orchestrating workflows using dbt Cloud, Matillion Data Productivity Cloud, Airflow, or Azure Data Facto
ry. 2. Comfortable working with data ingestion from cloud storage (e.g., Azure Data Lake, AWS  S3) and APIs, including building Matillion pipelines that consume REST APIs and leverage native SaaS connecto

rs.
◦ Data Modelling and Architect
ure:
1. Dimensional modelling (Star/Snowflake schemas), Slowly changing dimensi
ons.
2. Knowledge of modern data warehousing princip
les .3. Experience implementing Medallion Architecture (Bronze/Silver/Gold layers) using a combination of Matillion for inges tion and staging and dbt for downstream transformati
ons.
4. Experience working with Parquet, JSON, CSV, or other data form

ats.
◦ Programming Langu
age s:
1. P ython:
For data transformation, notebook development, automation, and extending Matillion via Python script compon
ent s.2 . SQL:
Strong grasp of SQL for querying and performance tu
nin g.3. J inja (nice to have):
Exposure to Jinja for advanced dbt develop

ment.
◦ Data Engineering & Analytical S
kills:
1. ETL/ELT pipeline design and optimization across dbt and Mati
llion.
2. Exposure to AI/ML data pipelines, feature stores, or MLflow for model tracking (good to
have).3. Exposure to data quality and validation frame

works.
◦ Security & Gove
rna nce:
1. Experience implementing data quality checks using dbt tests and Matillion validation com p
onents.
2. Data encryption, secure key management, and security best practices for Snowflake, dbt, and Matillion (credential management, OAuth, workspace/environment isol

ation).

• Soft Skills & Lea
dership:

Ability to thrive in client-facing roles with competing/changing priorities and fast-paced delivery
cycles.

Stakeholder Commu nication:
Collaborate with business stakeholders to understand objectives and convert them into actionable data engineering
designs.

Project O wnership:
End-to-end delivery including design, implementation, and mon
itoring.

Me ntorship:
Guide junior engineers and establish best practices;
Build new skill in t
he team.

Agile P ractices:
Work in sprints, participate in scrum ceremonies, story est

imation.

• E
ducation:◦ Bachelor’s or master’s degree in computer science, Data Engineering, or a relat
ed field.◦ Certifications such as Snowflake Snow Pro Advanced, dbt Certified Developer, and Matillion Associate or Professional Certification (Data Productivity Cloud) ar

e a plus.