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.
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.
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:
Model it into clean, reliable tables (orders, returns, vouchers, campaigns, creators, live sessions)
Power dashboards (S2), consumer insights (S3), and BI sprints (S4)
This role is perfect for someone with ~3 years of hands- on data engineering / analytics engineering who wants to own end- to- end data architecture in a growing product.
Ingest data from TikTok Shop, Shopee, and client systems
JOB DESCRIPTION
Build and run ELT pipelines
Design and implement batch & incremental pipelines from:
Handle backfills, retries, logging, and monitoring so we can trust the runs every day.
Client internal systems (sales, finance, CRM)
TikTok Shop & Shopee (API/CSV exports)
Work with Data Ops to move from manual CSV workflows to more automated flows over time.
Design and maintain the data warehouse
Optimize for performance and cost (partitioning, indexing, clustering, materializations).
Define schemas for facts and dimensions
Implement models in dbt (or similar) with a clear layer structure: stg_* → int_* → mart_*.
Data quality, lineage & documentation
Work closely with Analysts and Data Ops to catch issues early and prevent repeat problems.
Maintain clear lineage and data documentation (what each table/column means, grain, usage examples).
Implement data quality tests (freshness, null checks, uniqueness, referential integrity, reconciliation with platform/client totals).
Expose data for products & clients
Support Analysts in building fast, reliable dashboards on top of your models.
Provide stable views & tables for reports
Set up read- only SQL/API endpoints and scheduled exports (CSV/Parquet) for clients.
REQUIREMENT
Comfortable with Git (branches, merge requests) and Docker concepts.
Strong SQL (window functions, joins, aggregations on large tables).
~3 years experience as a Data Engineer / Analytics Engineer / similar.
Experience with at least one modern warehouse (ClickHouse, BigQuery, Snowflake, Postgres used as warehouse, etc.).
Experience using Airflow / Dagster to schedule and monitor jobs.
Solid Python for ETL and small data tools.
Experience with dbt or a similar SQL- based modeling framework.
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.
Knowledge of security & privacy basics (role- based access, masking, retention).
Familiar with APIs and building small internal services (e.g., FastAPI) to expose data.
BENEFIT
Full participation in Social Insurance, Health Insurance, Unemployment Insurance;
Salary: Negotiate;
Working in a dynamic and youthful environment, with high opportunities for career advancement.
12 days of annual leave per year;
13th- month salary, participation in Team Building, Year End Party, etc.;
