We are looking for a highly experienced and proactive Senior Data Engineer to join our growing team. This role involves working closely with client teams, especially ML engineers and product owners, to architect, optimize, and operationalize cutting-edge data and AI solutions.
Key Responsibilities
Provide technical leadership and guidance to clients across the data landscape.
Optimize and scale data pipelines, especially using Apache Spark.
Collaborate with client ML engineers to define and implement MLOps and LLMOps processes.
Support the productionization of Generative AI workflows; prior experience preferred or at least solid foundational knowledge.
Work on Databricks for advanced analytics and large-scale data processing — hands-on experience is mandatory.
Engage with client Product Owners (POs) to identify resource requirements, plan milestones, and manage cross-stream releases.
Lead and mentor a team of data engineers to ensure high-quality delivery and alignment with project goals.
Requirements
9–15 years of experience in data engineering with a strong focus on big data technologies.
Proven expertise in building and optimizing Spark-based data pipelines.
Strong exposure to machine learning workflows, MLOps tools, and collaboration with ML engineers.
Working knowledge or experience in GenAI and LLMOps is a plus.
Solid experience with Databricks is essential.
Strong stakeholder management skills with the...
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Skills
Data Engineer, SPARK, ML Ops, Gen AI, LLMOps, Databricks, AWS
📌 Data Engineer with ML (Bengaluru)
🏢 CoffeeBeans
📍 Bengaluru
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