Senior Data Engineer

Why Join HYCU? HYCU is the fastest-growing leader in the multi-cloud and SaaS data protection as a service industry. By bringing true SaaS-based data backup and recovery to on-premises, cloud-native, and SaaS IT environments, the company provides unrivaled data protection, migration, disaster recovery, and ransomware protection to thousands of companies worldwide. The company's award-winning R-Cloud platform eliminates complexity, risk, and the high cost of legacy-based solutions, providing data protection simplicity to make it the #1 SaaS Data Protection platform. With an industry leading NPS score of 91, HYCU has raised $140M in VC funding to date and is based in Boston, Mass. Learn more at www.hycu.com. Overview We are seeking a Data Engineer that will be responsible for designing, building, and maintaining data pipelines and platforms that ensure reliable, high-quality data availability for analytics and Generative AI use cases. We are building next-generation Generative AI products that deliver actionable data insights at enterprise scale. High-quality, reliable, and AI-ready data is foundational to our platform. Our data engineering team builds scalable data pipelines and platforms that power analytics, machine learning, and Generative AI systems . Location : B angalore , India (Hybrid; 3 days onsite/2 days remote) What You’ll Do: Design, build, and maintain scalable data ingestion, transformation, and enrichment pipelines Support batch and real-time data processing for analytics and AI workloads Ensure data quality, consistency, and availability across systems Enable AI-ready data by supporting feature stores, embeddings, and downstream consumers Collaborate with AI, analytics, and product teams to meet evolving data requirements Build and operate reliable data pipelines that support AI and analytics use cases Monitor data pipelines and proactively resolve data quality or performance issues Work with stakeholders to understand data requirements and deliver solutions Implement standards for data validation, documentation, and lineage Continuously improve data platform scalability and efficiency What We’re Looking For: Bachelor’s or Master’s degree in Computer Science , Engineering, or a related field 6–9 years of experience in data engineering or data platform roles Experience supporting analytics, ML, or AI-driven systems Exposure to large-scale, enterprise data environments is a plus Strong experience with data engineering and distributed data systems Hands-on experience with ETL/ELT pipelines and data transformation frameworks Experience working with cloud data platforms and data warehouses Knowledge of data quality, observability, and governance practices Proficiency in SQL and at least one programming language such as Python Technical Skills Required: Core Skills Python ETL / ELT pipelines Batch + event-driven processing Schema evolution handling Data validation techniques Tools (Preferred) Kafka / PubSub Airflow (nice-to-have) OpenSearch indexing pipelines Cloud storage (S3/GCS) FastAPI for ingestion endpoints Strong Bonus Data quality frameworks Incremental indexing strategies Large-scale reindexing experience Attributes of a Successful HYCUer in this role: Self-starter and strategic thinker who thinks outside the box Takes responsibility and ownership for driving successful outcomes. You’re results-driven with a winning attitude Team player! You have excellent people and management skills to interact with staff, colleagues, cross-functional teams and third parties Hands-on and builders' mentality with an entrepreneurial mindset and intrinsic motivation Obsessed with being customer-focused – We know our customers and are advocates for their voice and point of view across HYCU Intellectual curiosity, always open for continuous learning/growth mindset Who We Are: Our Core Values: Authenticity , Grit and Empathy are at the heart of everything we do at HYCU. All of us at HYCU take ownership in shaping and contributing