Data Engineer

Job Description

Role Overview :

As a Data Engineer II/III, you will be responsible for architecting and maintaining the high-scale data infrastructure that powers Rapido’s decision-making engines.

You will work closely with data scientists, product managers, and software engineers to build reliable data pipelines that process millions of daily transactions.

Your work will directly influence the efficiency of our dispatch algorithms, pricing models, and user experience, ensuring that our data platform remains scalable, performant, and accurate as we continue to expand our footprint across the country.

Key Responsibilities :

– Design and implement scalable data pipelines using Spark and Python to process large-scale streaming and batch data from diverse sources.

– Develop and optimize complex SQL queries and data models to support business intelligence reporting and advanced analytical use cases.

– Orchestrate complex data workflows using Apache Airflow to ensure timely availability and high data quality for downstream consumers.

– Manage and scale data infrastructure components on Kubernetes, ensuring high availability and cost-efficiency for our data processing clusters.

– Integrate real-time data streams using Kafka to enable low-latency insights for operational monitoring and dynamic pricing systems.

– Collaborate with cross-functional engineering teams to establish best practices for data governance, schema design, and system performance tuning.

Required Skillset :

– Proven ability to design and maintain robust data warehouses and data lakes that handle high-velocity data ingestion and complex transformations.

– Strong proficiency in Python and SQL, with a demonstrated track record of writing clean, maintainable, and highly performant code for production environments.

– Extensive experience in building distributed data systems using Spark and Kafka, with a deep understanding of performance optimization and troubleshooting.

– Demonstrated capability in managing containerized applications using Kubernetes, including deployment, monitoring, and scaling of data services.

– Excellent communication skills with the ability to translate complex technical requirements into actionable data solutions for non-technical stakeholders.

– Ability to thrive in a fast-paced, hybrid work environment in Bangalore, demonstrating ownership and a proactive approach to solving ambiguous engineering challenges.

– A degree in Computer Science, Engineering, or a related quantitative field, backed by 2 to 6 years of relevant experience in building large-scale data platforms.

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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