Databricks Data Engineer

As a Databricks Data Engineer, you will be responsible for designing, developing, and maintaining data solutions for data generation, collection, and processing in

Big Data environment using predominantly PySpark/Python.

Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL

processes to migrate and deploy data across systems using PySpark.

· Collaborate closely with data scientists, data engineers, and business stakeholders to gather requirements and understand the business objectives driving

data pipeline development.

· Design, develop, and maintain robust, scalable high-performance Data Pipelines using Databricks.

· Leverage Databricks features such as Lakehouse and Delta Lake for efficient data storage and Spark for distributed processing

· Develop ETL/ELT pipeline using Databricks

· Monitor pipeline health, troubleshoot data issues

· Migrate on Prem Pyspark, SAS data pipeline and ML Models to Databricks

· Define and implement best practices in Databricks

· Evaluate new Databricks features and tools, helping the organization stay at the forefront of innovation in AI and Big DataProven expertise in implementing Lakehouse and Delta Lake using Databricks. · Strong PySpark and Python experience · Databricks Certified Data Engineer Professional Certification · Familiarity with ML Ops/LLM Ops and distributed systems. · Experience with Big Data platform like Cloudera Hadoop and Could platforms like AWS, GCP. · Solid understanding of system design patterns, scalability, observability, and performance tuning. · Strong analytical and problem-solving skills. · Passion for exploring and building with emerging technologies. Good to Have Skills:

• AWS EKS Experience, Dockers and Containers