Job Title

EazyML, Recognized by Gartner, EazyML () specializes in Responsible AI. Our solutions facilitate proactive compliance and sustainable automation and The company is associated with breakthrough startups like Amelia.ai.This is a full-time Remote role for a Senior Databricks Engineer with experience in Snowflake.The person can work from home (anywhere in INDIA, job location is in India).We're hiring a Senior Databricks Engineer to design, build, and optimize scalable data platforms leveraging Databricks. Experience in Snowflake is mandatory. This role will be responsible for delivering reliable, high performance data pipelines and analytics-ready datasets, while providing technical leadership and mentoring within the data engineering team.Required Qualifications6+ years of experience in Data Engineering, ETL Development, Database Administration.Strong hands-on experience with Databricks in production environmentsAdvanced SQL skills and solid expertise in data modelingProficiency in Python, SQL, PySparkStrong experience with Apache Spark and PySparkExperience working with Delta Lake, schema evolution, and data versioningExperience with cloud platforms (AWS, Azure, or GCP)Experience building scalable, reliable, fault-tolerant data pipelinesSolid understanding of distributed data systemsExposure to ML pipelines or feature stores (Databricks Feature Store preferred)Key SkillsDatabricks & Apache SparkSnowflake data warehousingLakehouse and Data Warehouse architectureAdvanced SQL and performance tuningCloud-native data engineeringScalability, reliability, and cost optimizationTechnical leadership and mentoringDesign and implement scalable data pipelines using Databricks (PySpark, Delta Lake)Develop and optimize ELT pipelines loading data for analytics and reportingArchitect and maintain lakehouse and warehouse solutions following Bronze, Silver, and Gold data layer patternsBuild batch and streaming pipelines using Databricks Jobs and Spark Structured StreamingDesign data models optimized for Snowflake (star/snowflake schemas, dimensional modeling)Optimize Spark jobs and Snowflake queries for performance and cost efficiencyImplement data quality checks, monitoring, and data validation across Databricks and SnowflakeIntegrate Databricks and Snowflake with orchestration tools ( Azure Data Factory, etc. )Ensure data security, governance, role-based access control, and compliance standardsCollaborate with Data Analysts and Data Scientists to deliver analytics and ML-ready datasetsTroubleshoot complex pipeline failures and perform root-cause analysisMentor junior engineers, conduct code reviews, and enforce engineering best practicesContribute to data architecture decisions, tooling evaluation, and roadmap planningMaintain clear documentation of pipelines, data models, and system architectureExperience: 6+ years | CS/IT degree preferred