Job DescriptionExperience Required: 3-5+ Years

NCTC: 4.5-6 LPA

NEmployment Type: Full time

NAbout Gintaa:

NAt Gintaa, were redefining how India orders food. With our focus on affordability, exclusive restaurant partnerships, and hyperlocal logistics, we aim to scale across Indias Tier 1 and Tier 2 cities. Were backed by a mission-driven team and expanding rapidly, nows the time to join the core leadership and build something impactful from the ground up.

NKey Responsibilities:

NData Engineering & Pipeline Development

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- Design, build, and maintain scalable ETL/ELT data pipelines.
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- Develop real-time and batch ingestion workflows across PostgreSQL, MongoDB, Firestore, and BigQuery.
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- Implement CDC-based ingestion pipelines using Debezium and cloud-native architectures.
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- Ensure reliability, monitoring, validation, and reconciliation of production data workflows.
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nBigQuery & Analytics Engineering

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- Design optimized BigQuery datasets for high-volume analytical workloads.
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- Develop complex SQL transformations using joins, CTEs, window functions, aggregations, and event sequencing logic.
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- Build scalable analytical data models for reporting and business intelligence.
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- Optimize query performance and reduce analytical processing cost.
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nProduct Analytics & Event Processing

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- Work extensively with GA4 event-level datasets and behavioral analytics systems.
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- Build KPI frameworks, conversion funnels, cohort analysis, and drop-off tracking systems.
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- Engineer reusable analytics datasets for dashboarding and reporting.
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- Ensure metric correctness and event consistency across analytics systems.
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nRecommendation & Scoring Systems

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- Develop heuristicand weighted-scoring recommendation engines.
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- Implement seller scoring, item ranking, and operational performance tracking systems.
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- Optimize recommendationworkflows for scalability and maintainability.
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- Handle large-scale batch computation efficiently.
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nWeb Scraping & Data Enrichment

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- Build scraping pipelines using Selenium and BeautifulSoup.
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- Perform text preprocessing, normalization, cleaning, and transformation.
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- Enrich internal datasets using external structured and semi-structured sources.
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- Automate repetitive data collection and processing workflows.
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nProduction Reliability & Monitoring

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- Monitor and resolve production-level data pipeline issues.
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- Perform root cause analysis (RCA) for data inconsistencies and failures.
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- Implement validation and debugging mechanisms for critical analytics systems.
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- Ensure stability, scalability, and reliability of production analytics infrastructure.
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nPreferred Qualifications

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- Experience working with high-volume event-driven systems.
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- Strong understanding ofanalytics engineering and reporting layers.
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- Hands-on experience with funnel analysis and behavioral analytics.
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- Familiarity with distributed data processing and scalable architectures.
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- Problem-solving mindsetwith strong debugging capabilities.
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📌 Big Data Engineer (Secunderabad)
🏢 Gintaa
📍 Secunderabad