# Data Engineer résumé example

Six years of pipeline work in Indian fintech, including a contract stint, measured in freshness, cost and failed runs.

![Data Engineer résumé example — mid level, written for India, set in the Terminal design](https://cvaurum.com/img/examples/data-engineer.webp)

- Field: Data & Analytics
- Career stage: Mid level
- Written for: India
- Design: Terminal (https://cvaurum.com/templates/technical)
- Open it: https://cvaurum.com/examples/data-engineer

Every name, employer, address, phone number and figure below is invented.

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## Rohit Nambiar — Data Engineer

Data engineer with six years on high-volume financial and marketplace pipelines. Runs the ingestion layer behind 2.1 billion daily transaction events, and rebuilt a ledger reconciliation that took 14 hours into a stream that settles in nine minutes.

### Experience

**Data Engineer**, Arclane Financial Technologies · February 2023 – present

Platform team of eleven. Owns ingestion, the lakehouse and the data-quality gate in front of reporting.

- Owns the ingestion layer landing 2.1 billion transaction events a day; p95 freshness stayed under seven minutes through a threefold rise in volume.
- Replaced a nightly bulk dump with change-data capture, cutting the ledger reconciliation window from 14 hours to nine minutes.
- Cut cluster spend ₹48 lakh a year by moving 70 Spark jobs to autoscaling clusters and rewriting the three that shuffled 4 TB needlessly.
- Built the quality gate that blocks a bad partition before reporting sees it; it has caught 61 upstream schema changes in 18 months.

**Data Engineer (contract)**, Orenda Marketplace · April 2022 – January 2023

Ten-month fixed-term contract to stand up a first data warehouse.

- Delivered the first warehouse covering orders, payouts and sellers in nine months as the only data engineer on a four-person team.
- Wrote the orchestration framework the client still runs: 180 pipelines generated from YAML, with backfills that cost one command instead of a day.

**Associate Data Engineer**, Auralite Analytics · July 2020 – March 2022

- Built the nightly ETL for a media measurement product, processing 400 GB of viewership logs inside a 90-minute window.
- Took the nightly pipeline from one failed run in five to one in forty by making writes idempotent and retries safe to repeat.

### Education

- B.Tech. Computer Science and Engineering · National Institute of Technology Karnataka, Surathkal · July 2016 – May 2020

### Skills

- **Languages**: Python, Scala, SQL, Bash
- **Platform**: Spark, Kafka, Databricks, Airflow, AWS, Delta Lake
- **Pipelines**: Change data capture, Debezium, dbt, Data quality gates, Backfills
- **Practice**: Cost tuning, Schema evolution, On-call, Runbooks