Back
Tier-1 brand, metro location, mid-level generalist data role, and broad toolset increase competition.
Data engineering skills and tooling are broadly transferable across industries.
Explicit 5+ years requirement and mandatory data-platform tools enforce strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own and maintain multiple large-scale data pipelines and data products, ensuring reliability, scalability, and operational efficiency.
Develop and enhance data platform capabilities including monitoring, alerting, testing, and troubleshooting within the analytics ecosystem.
Act as main technical liaison for pipeline failures and data quality issues, delivering actionable metrics and recommendations to downstream teams.
Minimum 5 years of hands-on experience in data engineering or software engineering focusing on data pipelines.
Bachelor's degree in Computer Science, Engineering, Mathematics, or 5 years of equivalent progressive experience.
Proficiency in at least one programming language, preferably Java or Python.
Experience building production data pipelines in the cloud and working with data lakes, load balancing, caching, NoSQL, and tools like Flink, CDC, Kafka, Airflow, Snowflake, or DBT.
Experienced in end-to-end data pipeline ownership with a focus on reducing operational workload through innovation.
Comfortable collaborating with cross-functional teams across time zones, including engineering managers, product managers, and data scientists.
Strong background in big data at scale, schema design, data modeling, and statistical methods related to anomalies and A/B testing.