Data Engineer (Databricks & Snowflake)

We are looking for a Senior Data Engineer to design, build, and optimize scalable data platforms and pipelines. You will work closely with analytics, data science, and business teams to deliver reliable, high-quality data using modern cloud technologies. Hands-on expertise in Databricks and Snowflake is essential.

Key Responsibilities

• Design, develop, and maintain scalable batch and real-time data pipelines using Databricks (PySpark/Spark SQL) and Snowflake.
• Build and optimize ELT/ETL workflows to ingest data from diverse sources (databases, APIs, files, streaming platforms).
• Implement data lakehouse and data warehouse solutions following medallion architecture (Bronze/Silver/Gold).
• Optimize performance and cost across Databricks clusters and Snowflake warehouses.
• Develop and manage data models (dimensional, star/snowflake schemas) to support analytics and reporting.
• Implement data quality, validation, lineage, and governance frameworks.
• Set up CI/CD pipelines and infrastructure-as-code for data workflows.
• Orchestrate pipelines using tools such as Airflow, Azure Data Factory, or Databricks Workflows.
• Ensure data security, access controls, and compliance with organizational standards.
• Collaborate with data scientists, analysts, and product teams to translate requirements into technical solutions.
• Troubleshoot production issues and ensure pipeline reliability and SLA adherence.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 7+ years of experience in data engineering or related roles.
• Strong hands-on experience with Databricks (Spark, Delta Lake, Unity Catalog, Workflows, notebooks).
• Strong hands-on experience with Snowflake (Snowpipe, Streams & Tasks, Time Travel, virtual warehouses, RBAC, performance tuning).
• Advanced proficiency in SQL and Python (PySpark).
• Solid understanding of data warehousing, data modeling, and ETL/ELT concepts.
• Experience with at least one major cloud platform (AWS, Azure, or GCP).
• Experience with version control (Git) and CI/CD practices.
• Strong problem-solving, communication, and stakeholder management skills.

Preferred Qualifications

• Databricks or Snowflake certifications (e.g., Databricks Certified Data Engineer, SnowPro Core/Advanced).
• Experience with streaming technologies (Kafka, Event Hubs, Kinesis, Structured Streaming).
• Familiarity with Airflow, or similar transformation/orchestration tools.
• Exposure to ML/MLOps pipelines and feature engineering.
• Experience working in Agile/Scrum environments.