Data Engineer Data Quality & Platform

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 Youll 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 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 Youll 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