Immediate/Early Joiners preferred
We are seeking an experienced Senior Data Engineer with robust hands-on expertise in designing, developing, and optimising scalable data ingestion and processing pipelines using Databricks, PySpark, and AWS services.
Key Responsibilities
• Design and implement scalable batch and streaming data pipelines using Databricks and PySpark.
• Develop cloud-native data ingestion and ETL solutions using AWS streaming and data processing services.
• Implement Medallion Architecture (Bronze, Silver, and Gold layers) and modern Lakehouse solutions.
• Leverage Unity Catalogue for data governance, security, lineage, and metadata management.
• Integrate and support MLflow for machine learning lifecycle management and analytics use cases.
• Optimise
• pipeline performance, reliability, scalability, data quality, and cost efficiency.
• Collaborate with data science, analytics, and business teams to deliver reliable data solutions.
• Participate in technical design, code reviews, CI/CD, and engineering best practices.





Required Skills & Expertise
• Databricks and PySpark
• AWS Streaming and ETL Services
• Unity Catalog and MLflow
• Medallion Architecture and Lakehouse Architecture
• SQL, Data Modelling, and Data Lake concepts
• Strong experience in enterprise-scale data ingestion and processing pipelines

Good to Have
• Python scripting and automation
• Pandas for data transformation and analysis
• Workflow orchestration using Airflow or Databricks Workflows
• Exposure to DataOps/MLOps practices and CI/CD implementation

Ideal Candidate
A hands-on Data Engineer with 6–8 years of relevant experience, strong problem-solving skills, and the ability to build secure, governed, scalable, and cost-efficient data platforms.
? Interested candidates can share their updated CV at [email protected]
Hiring #SeniorDataEngineer #DataEngineering #Databricks #AWS #PySpark #ETL #DataPipelines #LakehouseArchitecture

📌 Senior Data Engineer – Databricks (Pune)
🏢 RefRelay
📍 Pune