You'll work directly alongside our existing Data Engineer, own your work end-to-end, and see the impact of what you build within days. This is not a support role.

Responsibilities

• Design, build, and maintain ELT/ETL pipelines that ingest data from external platforms, APIs, and web-based sources into BigQuery
• Develop reliable data flows across our four-layer architecture: Raw → Staging → Mart → Semantic with clear ownership of grain, keys, deduplication, and table design
• Write Python-based ingestion and processing jobs with validation, error handling, and production-grade reliability
• Design pipelines with idempotency, rerun safety, backfill handling, monitoring, and failure recovery built in from the start
• Handle messy, unstable, or poorly documented external data sources (schema drift, missing keys, duplicate records, inconsistent formats)
• Implement data quality checks for completeness, uniqueness, schema validation, and cross-run consistency
• Optimize BigQuery queries and tables using partitioning, clustering, and cost-aware SQL patterns
• Collaborate with the Analytics Lead and the BI analyst to ensure data reaching the commercial team is clean, timely, and trustworthy

Requirements

• 3-5 years of experience with at least 2 years in data engineering or production data pipeline development
• Strong Python skill (production pipelines, API ingestion, validation, debugging)
• Strong SQL skill (complex transformations, deduplication, merge/upsert, performance tuning)
• Hands-on experience with at least one major cloud platform such as GCP, AWS, or Azure; GCP experience is preferred but not mandatory
• Experience with workflow orchestration tools such as Airflow, Prefect, Dagster, or cloud-native schedulers; Airflow experience is preferred
• Solid understanding of data modeling: grain, business keys, staging/mart layers, deduplication logic
• Experience building pipelines designed for idempotency, rerun safety, and auditability
• Ability to work with imperfect, undocumented data sources and design practical solutions
• Git-based workflows and Linux command-line comfort
• Startup or high-growth environment experience — you own your outcomes

Nice to Have

• Hands-on experience with GCP services such as BigQuery, GCS, Cloud Run, Cloud Functions, Cloud Scheduler, Dataflow, or service accounts
• Experience with Airflow DAG design, backfills, retries, task dependencies, external triggers, and production operations
• Experience extracting data from external systems through APIs, authentication flows, pagination, rate limits, file downloads, or web automation
• Experience with Selenium, Playwright, or similar tools for data extraction
• Familiarity with Dataform, dbt, or similar transformation-layer management tools
• Comfort working with messy, undocumented legacy pipelines

About N-Infinite

N-Infinite is a food tech company focused on helping restaurants grow their delivery sales through smart, data-driven solutions. We work closely with leading restaurant brands to strengthen their delivery performance and expand customer reach. Our machine learning and analytics tools integrate seamlessly with major delivery platforms such as Grab, Shopee Food and LINE MAN Wongnai, enabling our partners to improve visibility, optimize operations, and drive sustainable growth across channels.

Our team thrives in a fast-paced, collaborative environment that encourages creativity and continuous learning. We provide opportunities to develop skills in data analytics, marketing, and creative content, while building meaningful impact in the food tech space.

At N-Infinite, innovation, adaptability, and growth are at the heart of what we do.