Senior Data Engineer

Overview

We are looking for a highly skilled Senior Data Engineer to design, build, and optimize scalable data pipelines and data platforms. The ideal candidate will have strong experience in cloud-based data architectures, big data processing, and modern data warehousing solutions. You will play a key role in enabling data-driven decision-making across the organization.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines to process large volumes of structured and unstructured data
• Build and optimize data pipelines using PySpark, Spark, and Python
• Develop robust data solutions on AWS (S3, Glue, Lambda, Redshift, EMR)
• Implement and manage data workflows using Databricks
• Design and maintain data models and warehouses in Snowflake
• Ensure data quality, integrity, and governance across all data systems
• Optimize data processing performance and cost efficiency in cloud environments
• Collaborate with data scientists, analysts, and business stakeholders to deliver reliable data solutions
• Monitor, troubleshoot, and improve existing data pipelines and workflows
• Implement best practices for data security, compliance, and scalability

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• 6+ years of experience in data engineering or related roles
• Strong programming skills in Python
• Hands-on experience with Apache Spark and PySpark
• Extensive experience with AWS data services (S3, Glue, EMR, Lambda, Redshift)
• Solid experience with Snowflake data warehouse
• Experience working with Databricks platform
• Strong understanding of ETL/ELT frameworks and data pipeline design
• Experience with SQL and data modeling techniques
• Familiarity with workflow orchestration tools (Airflow, Step Functions, etc.)
• Knowledge of data governance, security, and compliance best practices

Preferred Qualifications

• Experience with real-time/streaming data processing (Kafka, Kinesis)
• Knowledge of CI/CD pipelines and DevOps practices
• Experience with containerization (Docker, Kubernetes)
• Exposure to data lake and lakehouse architectures
• Certification in AWS or Snowflake is a plus