Data Engineer

Job Description

About Zocket: AI Assistant for Marketers Zocket empowers businesses to scale social media advertising seamlessly with advanced AI . From search to conversions, Zocket automates the entire workflow effortlessly. Headquartered in Chennai and San Francisco , with 500+ customers across 25+ countries. Our GenAI Product Suite: Creative Studio: Make ad creatives 10x faster, 20x better Audience Assistant: Precision targeting, platform-wide Snoop AI: Competitive & industry insights in seconds Insights AI: 360 performance dashboard across channels Growth Infra: Whitelisted infra for unbounded scale Trusted and Recognized: AWS GenAI Accelerator 2024 (Top 80 global startups) Google for Startups (GFSA Class VIII Ai-first) NASSCOM Gen AI Foundry 4.9 Trustpilot | #1 Product of the Day & Week on Product Hunt Key Responsibilities Design, build, and maintain robust ETL pipelines to process large-scale structured and unstructured data. Work with GraphQL databases and Vector DBs (e.g., Pinecone, Chroma) to power intelligent, AI-driven features. Build and optimize scalable ML pipelines and contribute to model lifecycle management . Implement real-time and batch data streaming solutions using Kafka and Spark . Work with Airflow to schedule and orchestrate data workflows. Develop efficient data models in PostgreSQL and ensure high-performance data access. Integrate and optimize Elasticsearch for fast search and analytics. Ensure high data quality and reliability through monitoring and automation. Collaborate with Product, Data Science, and Engineering teams to deliver scalable data solutions. Own the data infrastructure on AWS - from data lake to warehouse and analytics stack. Drive internal data tooling improvements and support analytics for business decision-making. Key Requirements 4-5 years of experience as a Data Engineer or in a similar backend/data-intensive role. Strong programming experience with Python and familiarity with ML model development workflows . Hands-on experience with GraphQL and Vector DBs (Pinecone, Chroma). Proficiency in PostgreSQL and working knowledge of NoSQL and search systems like Elasticsearch . Solid understanding of data engineering on AWS (EC2, S3, RDS, Redshift, etc.). Experience with Apache Kafka , Apache Spark , and Airflow is essential. Familiarity with modern ML Ops and data science integration is a plus. Strong analytical thinking and problem-solving skills.