As a
Data Engineer
, you will play a vital role in bridging the gap between data engineering and analytics to deliver actionable insights that drive strategic decisions. You will design, build, and optimize scalable data pipelines, data models, and dashboards that enable business teams to make data-driven decisions with confidence
You'll collaborate closely with cross-functional teams—including marketing, sales, and operations—to transform raw data into valuable business intelligence, particularly in the fast-paced
beauty and FMCG
industries where data-driven insights are key to consumer understanding and growth.
Key Responsibilities
- Design, develop, and maintain
data pipelines
and
ETL processes
using
Airflow
,
Python
, and
Google Cloud Platform (GCP)
tools. - Build and optimize
data warehouses
in
BigQuery
, ensuring data integrity, scalability, and performance. - Develop and maintain
Power BI dashboards
to provide key business metrics, trend analysis, and performance insights. - Collaborate with business stakeholders to understand analytical needs and translate them into efficient data models and solutions.
- Implement
data modeling
best practices (star/snowflake schemas) to support analytics and reporting. - Apply
query optimization
and performance-tuning techniques to enhance system efficiency. - Ensure high data quality, consistency, and governance across data systems.
- Work cross-functionally with marketing, sales, and finance teams to provide insights that support campaign performance, product launches, and market expansion.
Requirements
- Strong proficiency in SQL (BigQuery)
and
Python
for data processing, transformation, and automation. - Hands-on experience with
Airflow
,
Docker
, and
Google Cloud Platform
services (
BigQuery
,
Data Fusion
,
GCS
). - Skilled in building dynamic and insightful
Power BI dashboards
and reports. - Solid understanding of
data modeling principles
(star/snowflake schemas) and
query optimization
techniques. - Strong analytical thinking, problem-solving skills, and attention to detail.
- Excellent communication and collaboration skills with both technical and business stakeholders.
Preferred Qualifications
- Bachelor's degree in
Computer Science
,
Data Engineering
,
Statistics
, or a related field. - 3+ years of experience in
data analytics engineering
,
data warehousing
, or
business intelligence
roles. - Experience working in the
beauty
,
cosmetics
, or
FMCG
industries, with an understanding of sales, marketing, and consumer analytics. - Familiarity with version control tools (e.g., Git) and CI/CD pipelines.
- Experience with other BI tools (e.g., Looker, Tableau) is an advantage.