Data Engineer II
Yum! Brands (company site, opens in a new tab)7+ yrsGurugramRemoteDirect career pageEst. 24–38 LPA
Posted 18h ago
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Job description
Structured overview of role & requirements
About This Role
- Own complex Databricks/Spark data solutions from requirements and design through production support, including scalable batch and near-real-time pipelines.
- Build lakehouse data layers and analytical models; improve workload performance, reliability, cost, and downstream reporting usability.
- Establish reusable engineering patterns and data-quality controls, while guiding technical design, code reviews, and other engineers.
Minimum Requirements
- Work Experience Required: The JD gives conflicting requirements: 7+ years in data engineering or a related discipline in one section, and 3–6 years in another; it also specifies 3+ years developing production solutions with Databricks and Apache Spark.
- A BE is specified in the final required-qualifications section; no other degree requirement is stated.
- Hands-on Databricks, Apache Spark, Delta Lake, SQL, and Python/PySpark experience; demonstrated complex ETL/ELT pipeline delivery and dimensional data modeling.
- Experience with large-volume datasets, workload optimization, and data validation, reconciliation, monitoring, and production support.
Ideal Candidate Profile
- A hands-on senior engineer who can independently own technical solutions end to end while providing design direction and mentoring others.
- Strong lakehouse and enterprise analytics background, especially translating operational sources into reliable, business-oriented models for reporting and data products.
- Effective in complex production environments requiring reusable standards, performance tuning, data governance, and collaboration across distributed engineering, architecture, BI, and business teams.