Data Platform Engineer (Mid-Senior Level/ MRT Samyan)

About the Role

We're building out FlowAccount's data platform on top of our production stack (Clean Architecture / DDD / Akka.NET backend, domain events over RabbitMQ, Redshift as the analytics warehouse). This role owns the pipelines that move data from our operational services into the warehouse and keep it trustworthy, fast, and well-modeled.

This is a platform-ownership role, not a BI/reporting role — you'll work closely with Analytics Engineers and BO stakeholders, but your primary output is pipeline and warehouse architecture, not dashboards or ad-hoc queries.

What You'll Own

• Build and maintain ELT pipelines from operational databases (SQL Server) and domain events (RabbitMQ) into Redshift
• Write and maintain dbt models and tests; own data-quality checks and freshness SLAs
• Work in AWS: S3 (staging/lake), Glue/DMS for ingestion, Lambda/Step Functions for orchestration, CloudWatch for monitoring
• Consume and reason about domain events (e.g. JournalEntryCreated-style events) — not just batch table dumps
• Participate in on-call rotation for pipeline/data incidents

Mid (3–5 years)

• Implement pipelines and dbt models to a given design spec
• Maintain and extend existing Redshift schemas
• Handle defined CDC jobs and respond to data-quality alerts

Senior (6+ years) — in addition to the above

• Own warehouse schema/model design (star/snowflake, SCD strategy, partitioning, dist-key/sort-key strategy for cost and performance)
• Define data contracts with backend/DDD service owners — event schema versioning, breaking-change policy, deprecation process
• Own the data-quality/SLA framework end-to-end, including DLQ handling for failed event consumption and incident runbooks
• Make build-vs-buy calls on orchestration tooling; mentor Mid-level engineers

New-Data Intake (how this role interacts with Analytics Engineering)

When BO/Analytics Engineering needs a new event or data source tracked that doesn't exist in the warehouse yet, this role owns turning that request into reality:

• Receive data requirement specs from the Analytics Engineer (what event, what fields, why)
• Determine whether the source data already exists upstream (product/backend event) or needs new instrumentation — coordinate with the owning backend team if instrumentation is needed
• Build/extend the ingestion pipeline and warehouse schema to land the new data
• Hand off to Analytics Engineering once the data is queryable

You own how new data gets into the warehouse. Analytics Engineering owns what data is needed and why.

Requirements

• Strong SQL (Redshift or another columnar/MPP warehouse)
• Python or Spark for pipeline/transformation work
• Experience with dbt and an orchestrator (Airflow, Dagster, or equivalent)
• Experience with streaming/event-driven ingestion (Kafka, Kinesis, MSK, or RabbitMQ), not just batch ETL
• Familiarity with AWS data services (S3, Glue, Lambda, Step Functions)
• (Senior) Track record owning data-model design and cross-team data contracts

Preferred

• Experience with CDC tools (DMS, Debezium)
• Experience handling PII/financial data under a compliance regime (PDPA or equivalent) — including tenant/row-level isolation in a multi-tenant warehouse
• Prior experience in a DDD/microservices backend environment

What We Offer

• Build products used by tens of thousands of businesses.
• Ship code that reaches customers quickly.
• High ownership with minimal bureaucracy.
• Learn from experienced engineers and product leaders.
• Flexible work hours and 45 days/year work from anywhere.
• Competitive compensation, health & accident insurance from day one.
• 17–19 public holidays, 12 personal leave days, and 8 annual leave days.
• A friendly, collaborative team that genuinely enjoys building together.
• Clear opportunities to grow your career as the company scales.

Location

• BKK BangRak Office (MRT Samyan or BTS Saladaeng)

Why join us:

🚀 Work with a modern tech stack | 💡 Impact thousands of users | 🤝 Collaborative, growth-oriented team