Data Engineer

1 week ago

Ho Chi Minh City, Ho Chi Minh, Vietnam VIBULA Full time ₫1,200,000 - ₫3,600,000 per year

ABOUT VIBULA

Vibula is a trailblazing
Social Commerce

company in Vietnam, renowned for its
TikTok MCN

services and status as an official
TikTok Shop Partner (TSP)

. Beyond TikTok, we serve as a trusted
e-commerce enabler for Shopee, TikTok, and Lazada

, empowering Sellers and Creators to excel across these platforms and other social media channels. As a key connector between TikTokers and TikTok's ecosystem, Vibula drives channel management and delivers trend-driven content creation. We also provide Sellers with end-to-end solutions, including Livestream production, short-form videos, and strategic execution support to boost their success on leading e-commerce platforms.

You will be the key person who builds and maintains our data warehouse and data pipelines so that analysts, product and clients can trust the numbers every single day.

ROLES SUMMARY

You will be the
core Data Engineer

in a small, high-impact team (2 Data Analysts + 1 Data Ops). Your job: design and build the
data warehouse & pipelines

that:

  • Ingest data from
    TikTok Shop, Shopee, and client systems
  • Model it into clean, reliable tables (orders, returns, vouchers, campaigns, creators, live sessions)
  • Power dashboards, consumer insights, and BI sprints

This role is perfect for someone with 1~3 years of hands-on
data engineering / analytics engineering

who wants to own
end-to-end data architecture

in a growing product.

KEY RESPONSIBILITIES

1. Build and run ELT pipelines

  • Design and implement
    batch & incremental pipelines

from:
- TikTok Shop & Shopee (API/CSV exports)
- Handle
backfills, retries, logging, and monitoring

so we can trust the runs every day.
- Work with Data Ops to move from
manual CSV workflows

to more automated flows over time.

2. Design and maintain the data warehouse

  • Define schemas for
    facts and dimensions
  • Implement models in
    dbt (or similar)

with a clear layer structure

3. Data quality, lineage & documentation

  • Implement
    data quality tests

(freshness, null checks, uniqueness, referential integrity, reconciliation with platform/client totals).
- Maintain clear
lineage

and
data documentation

(what each table/column means, grain, usage examples).
- Work closely with Analysts and Data Ops to catch issues early and prevent repeat problems.

4. Expose data for products & clients

  • Provide
    stable views & tables

for reports
- Set up
read-only SQL/API endpoints

and
scheduled exports

(CSV/Parquet) for clients.
- Support Analysts in building fast, reliable dashboards on top of your models.

REQUIREMENTS

  • 1-3 years

experience as a Data Engineer / Analytics Engineer / similar.
- Strong
SQL

(window functions, joins, aggregations on large tables).
- Solid
Python

for ETL and small data tools.
- Experience with at least one modern
warehouse

(ClickHouse, BigQuery, Snowflake, Postgres used as warehouse, etc.).
- Experience with
dbt

or a similar SQL-based modeling framework.
- Experience using
Airflow / Dagster

to schedule and monitor jobs.
- Comfortable with
Git

(branches, merge requests) and
Docker

concepts.

NICE TO HAVE

  • Experience with
    ecommerce / social commerce data

(orders, returns, vouchers).
- Worked with
BI tools

(Metabase, Superset, Power BI, FineBI/FineReport, etc.).
- Exposure to
Airbyte / Meltano / Great Expectations

or similar.
- Familiar with
APIs

and building small internal services (e.g., FastAPI) to expose data.
- Knowledge of
security & privacy

basics (role-based access, masking, retention).

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