Data Engineer Data Quality & Platform

Job Description

Or Client is building a real-time data platform that powers core product decisions and customer-facing systems.

This role is for engineers who:

Own data pipelines end-to-end

Care deeply about data correctness

Can debug real production issues, not just monitor systems

You’ll work on high-scale, event-driven pipelines and ensure data is reliable, accurate, and trusted across the business.

Responsibilities

Own and operate data pipelines (ingestion transformation serving)

Debug and resolve data issues in production (latency, inconsistencies, failures)

Build scalable pipelines using Spark, Airflow, DBT, Kafka/CDC

Ensure data quality and reliability across systems

Work closely with product and analytics teams to ensure correct business metrics

Improve automation, monitoring, and observability of data systems

Ideal Profile

You have atleast 4 years' experience in data engineering / data platform roles

Strong hands-on experience with SQL (advanced), Spark / PySpark and Airflow (or similar)

Experience building and debugging production-grade data pipelines

Strong understanding of Data modeling, ETL/ELT systems and Data quality challenges

Ownership mindset, someone who fixes problems end-to-end

Why Join Us

High ownership- you build, run, and improve what you ship

Opportunity to shape data reliability and platform foundations