Description

You will architect scalable cloud-native data platforms using Snowflake and Databricks, leading enterprise modernization and migration initiatives from legacy systems.

This role is hybrid.

Responsibilities

• Design scalable data lake and warehouse architectures supporting analytics and reporting workloads.
• Build and optimize ETL/ELT pipelines for structured and semi-structured data processing.
• Implement data ingestion, transformation, orchestration, and governance frameworks.
• Develop high-performance Spark/Databricks solutions for large-scale data processing.
• Design and implement CI/CD pipelines and Infrastructure-as-Code (IaC) solutions.

Required Skills

• 10+ years of experience in Data Engineering, Big Data, or Cloud Data Architecture.
• Strong hands-on experience with Snowflake architecture, administration, and optimization.
• Extensive experience with Databricks, Apache Spark, and PySpark development.
• Strong expertise in designing enterprise data warehouses and data lakes.
• Proficiency with cloud platforms such as AWS, Azure, or GCP.
• Experience with orchestration tools such as Airflow, Azure Data Factory, or similar.
• Strong SQL and performance tuning experience.
• Experience with CI/CD tools and DevOps practices.
• Knowledge of data governance, security, and compliance frameworks.

Preferred Skills

• Experience with semi-structured data formats such as JSON, XML, Avro, and Parquet.
• Experience with Git, Agile methodologies, and SDLC best practices.

Key Skills

Education

Bachelor's degree