𝗪𝗲’𝗿𝗲 𝗵𝗶𝗿𝗶𝗻𝗴: 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿We are looking for a skilled and driven 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 to help build and operate scalable data pipelines for high-volume transaction data.
In this role, you will work across ingestion, processing, orchestration, data warehousing, and analytics enablement. You will play a key role in ensuring reliable, accurate, and well-structured data across the platform.𝗪𝗵𝗮𝘁 𝘆𝗼𝘂’𝗹𝗹 𝗱𝗼
- Design, build, and maintain ETL/ELT pipelines for payment transaction data from multiple sources
- Work with GCS, webhooks, Pub/Sub, APIs, SFTP, and email-based ingestion flows
- Develop Python-based ingestion and processing jobs using Google Cloud Functions and Cloud Run
- Build FastAPI services for webhooks and data APIs
- Own BigQuery warehouse layers from staging to mart using Dataform
- Implement and maintain Google Cloud Workflows for multi-step pipeline orchestration
- Partner with application teams on data contracts for APIs and admin tools
- Support ML workflows and analytics use cases
- Write clean, testable, and well-documented SQL and Python
- Monitor pipeline health, data freshness, and reconciliation
- Troubleshoot production issues and drive root-cause analysis
- Contribute to CI/CD improvements using GitHub Actions
- Document pipeline architecture and dataset semantics𝗪𝗵𝗮𝘁 𝘄𝗲’𝗿𝗲 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿
- 3+ years of professional data engineering or analytics engineering experience
- Strong proficiency in Python 3.10+ for data pipelines
- Experience with pandas, polars, and Python packaging tools such as Poetry
- Advanced SQL skills and hands-on BigQuery experience
- Experience with partitioning, clustering, incremental loads, and cost-aware query design
- Experience building batch and event-driven pipelines on Google Cloud Platform
- Solid understanding of dimensional modeling and layered warehouse design
- Experience with workflow orchestration and dependency management
- Strong experience with MySQL, PostgreSQL, and MongoDB
- Understanding of data quality practices such as schema validation, idempotency, deduplication, reconciliation, and backfills
- Experience with Git-based workflows and CI/CD for data deployments
- Strong problem-solving skills and comfort operating data systems in production𝗡𝗶𝗰𝗲 𝘁𝗼 𝗵𝗮𝘃𝗲
- Experience in fintech, payments, PSP integrations, or high-volume transaction analytics
- Hands-on experience with Dataform, including SQLX, assertions, incremental tables, and environment variables
- Exposure to Looker or similar BI layers
- Experience with FastAPI data services deployed on Cloud Run
- Knowledge of observability for data systems, including OpenTelemetry, structured logging, and GCP Trace/Logging
- Comfort working in Jupyter notebooks for exploratory analysis and ad hoc investigations𝗧𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸Python · SQL · BigQuery · Dataform · Google Cloud Platform · Cloud Functions · Cloud Run · GCS · Pub/Sub · Workflows · FastAPI · MySQL · PostgreSQL · MongoDB · GitHub Actions · Looker · JupyterIf this sounds like you, we’d love to hear from you.
