Data Engineer

At Finkraft.ai, we’re not just building a company — we’re reshaping how enterprises manage travel spends and GST credit. Trusted by 100+ Fortune 500 companies, we’re scaling fast and looking for someone exceptional to join us at the very heart of our journey.

What you’ll do

• Design & build ETL/ELT for batch + (where needed) streaming using PySpark.
• Orchestrate with a scheduler; add retries/alerts and simple SLAs.
• Own data modeling: craft ERDs; choose star/snowflake/data-vault patterns; design for performance (partitioning, clustering, distribution, indexing).
• Be architecture-aware (warehouse, lakehouse, lambda/kappa) and pick the right fit.
• Work with formats/schemas: Parquet, Avro, JSON (schema evolution, compression).
• Build on AWS (must-have); exposure to Azure/GCP is a plus.
• Deliver to Snowflake / BigQuery / Redshift; tune for cost & speed.
• Add traceability: data-quality checks, lineage, freshness SLAs, alerting.
• Own pipelines end-to-end for features/products; document; mentor juniors.

Who you are

• 3–5 yrs data engineering with Python (you code).
• Strong PySpark; solid Kafka/Beam fundamentals are a plus.
• Production scheduling/orchestration experience; dbt familiarity welcome.
• Deep in dimensional modeling (star/snowflake), data vault basics, and normalization vs denormalization trade-offs.
• Performance-first mindset for large/bulky data; excellent SQL; pragmatic with Mongo/NoSQL when needed.

Nice to have

• Azure Data Factory / GCP Dataflow; Kafka Connect; Delta/Iceberg; warehouse tuning stories.

To take the next step, please fill out this short form so we can get to know you and your work better:

👉: https://finkraft.typeform.com/to/F1e4Fv4D

Once submitted, Our team will review your application and connect with you on the next steps.

Looking forward to your submission!