We build web-data analytics products that turn messy public Web data into actionable insights for product, risk, and market-intel teams. We’re looking for a Data Engineer to strengthen our core data fetching and analysis pipelines.
You will:
- Expand our serverless data-fetching engine to collect more and richer web data.
- Design and implement analytical pipelines with ETL/ELT (dbt) and Apache Airflow/Dagster.
- Ensure test coverage and data quality/observability (freshness, schema, anomalies).
- Implement CI/CD and infra as code for data/ML services.
- Help shape the engineering culture (standards, reviews, docs).
Must-have:
- 3+ years in backend/data engineering.
- Working knowledge of Git & GitHub.
- Python and SQL.
- Bash and containerization (Docker).
- Serverless (AWS Lambda or GCP Cloud Functions).
- NoSQL (e.g., AWS DynamoDB, Bigtable, or Firestore).
- ETL/ELT (e.g., AWS Glue, dbt, or Apache Beam).
- Good command of English; proactive about proposing new solutions.
Nice-to-have:
- Terraform / IaC, Kubernetes.
- Big Data (e.g., Apache Spark/Flink), streaming (Kafka/Pub/Sub).
- Web scraping at scale (Scrapy/Playwright) and anti-bot resilience.
- Cost optimization/FinOps and data lineage tooling.
We offer:
- High degree of independence and ownership.
- Flexible, results-oriented role (remote/hybrid, CET±2).
- Real product impact and say in architecture/tooling.
- ESOP, learning budget, modern hardware, team offsites.
Apply: Send your CV/LinkedIn (+ GitHub/portfolio) to hello@banachastreet.com with subject “Data Engineer – Your Name”.