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Tier-1 brand, Bangalore, mid-senior data engineering role attract high candidate competition.
Cloud data engineering skills are transferable but consulting delivery experience moderately limits cross-industry fit.
Explicit 8-10 year requirement plus mandatory cloud, data-lake, ETL, and leadership skills raises strictness.
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Lead design and implementation of scalable cloud-based data engineering solutions including data lakes and ETL/ELT pipelines.
Drive pre-sales activities including client discussions, technical proposals, solution design, and PoCs.
Manage and mentor data engineering teams while ensuring successful project delivery aligned with client and business objectives.
5+ years of hands-on experience in Data Engineering and cloud-based data solutions.
Strong expertise with AWS, Azure, or Google Cloud Platform including data lakes.
Experience with Apache Spark, Databricks, AWS Glue, Azure Data Factory, or similar ETL tools and serverless computing technologies.
Work Experience Required: 8-10 years as explicitly mentioned in the JD.
Experienced technical leader capable of managing end-to-end pre-sales to delivery lifecycle in data engineering projects.
Strong background in designing secure and scalable data architectures on cloud platforms with cost optimization focus.
Proficient in cross-functional collaboration with data science, BI teams, and business stakeholders to enable reliable analytics and data governance.