๐ช๐ฒโ๐ฟ๐ฒ ๐ต๐ถ๐ฟ๐ถ๐ป๐ด: ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ
We are looking for a skilled and driven ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ 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.
๐ช๐ต๐ฎ๐ ๐๐ผ๐โ๐น๐น ๐ฑ๐ผ
โข Design, build, and maintain ETL/ELT pipelines for payment transaction data from multiple sources
โข Work with GCS, webhooks, Pub/Sub, APIs, SFTP, and email-based ingestion flows
โข Develop Python-based ingestion and processing jobs using Google Cloud Functions and Cloud Run
โข Build FastAPI services for webhooks and data APIs
โข Own BigQuery warehouse layers from staging to mart using Dataform
โข Implement and maintain Google Cloud Workflows for multi-step pipeline orchestration
โข Partner with application teams on data contracts for APIs and admin tools
โข Support ML workflows and analytics use cases
โข Write clean, testable, and well-documented SQL and Python
โข Monitor pipeline health, data freshness, and reconciliation
โข Troubleshoot production issues and drive root-cause analysis
โข Contribute to CI/CD improvements using GitHub Actions
โข Document pipeline architecture and dataset semantics
๐ช๐ต๐ฎ๐ ๐๐ฒโ๐ฟ๐ฒ ๐น๐ผ๐ผ๐ธ๐ถ๐ป๐ด ๐ณ๐ผ๐ฟ
โข 3+ years of professional data engineering or analytics engineering experience
โข Strong proficiency in Python 3.10+ for data pipelines
โข Experience with pandas, polars, and Python packaging tools such as Poetry
โข Advanced SQL skills and hands-on BigQuery experience
โข Experience with partitioning, clustering, incremental loads, and cost-aware query design
โข Experience building batch and event-driven pipelines on Google Cloud Platform
โข Solid understanding of dimensional modeling and layered warehouse design
โข Experience with workflow orchestration and dependency management
โข Strong experience with MySQL, PostgreSQL, and MongoDB
โข Understanding of data quality practices such as schema validation, idempotency, deduplication, reconciliation, and backfills
โข Experience with Git-based workflows and CI/CD for data deployments
โข Strong problem-solving skills and comfort operating data systems in production
๐ก๐ถ๐ฐ๐ฒ ๐๐ผ ๐ต๐ฎ๐๐ฒ
โข Experience in fintech, payments, PSP integrations, or high-volume transaction analytics
โข Hands-on experience with Dataform, including SQLX, assertions, incremental tables, and environment variables
โข Exposure to Looker or similar BI layers
โข Experience with FastAPI data services deployed on Cloud Run
โข Knowledge of observability for data systems, including OpenTelemetry, structured logging, and GCP Trace/Logging
โข Comfort working in Jupyter notebooks for exploratory analysis and ad hoc investigations
๐ง๐ฒ๐ฐ๐ต ๐๐๐ฎ๐ฐ๐ธ
Python ยท SQL ยท BigQuery ยท Dataform ยท Google Cloud Platform ยท Cloud Functions ยท Cloud Run ยท GCS ยท Pub/Sub ยท Workflows ยท FastAPI ยท MySQL ยท PostgreSQL ยท MongoDB ยท GitHub Actions ยท Looker ยท Jupyter
If this sounds like you, weโd love to hear from you.