We are seeking a highly skilled and motivated Senior Big Data Engineer to join our data team. The ideal candidate will play a key role in designing, developing, and maintaining scalable big data solutions while providing technical leadership. This role will also support strategic Data Governance initiatives, ensuring data integrity, privacy, and accessibility across the organization.

Key Responsibilities:

• Design, implement, and optimize robust data pipelines and ETL/ELT workflows using SQL and Python.
• Lead architecture discussions, including the creation and review of ERDs and overall system design.
• Collaborate closely with Data Engineers, Analysts, and cross-functional engineering teams to meet evolving data needs.
• Build synchronous and asynchronous data APIs for downstream systems to consume the data.
• Deploy and manage infrastructure using Terraform and other Infrastructure-as-Code (IaC) tools.
• Develop and maintain CI/CD pipelines for deploying data applications and services.
• Leverage strong experience in AWS services (e.g., S3, Glue, Lambda, RDS, Lake Formation) to support scalable and secure cloud-based data platforms.
• Handle both batch and real-time data processing effectively.
• Apply best practices in data modeling and support data privacy and data protection initiatives.
• Implement and manage data encryption and hashing techniques to secure sensitive information.
• Ensure adherence to software engineering best practices including version control, automated testing, and deployment standards.
• Lead performance tuning and troubleshooting for data applications and platforms.

Required Skills & Experience:

• Strong proficiency in SQL for data modeling, querying, and transformation.
• Advanced Python development skills with an emphasis on data engineering use cases.
• Hands-on experience with Terraform for cloud infrastructure provisioning.
• Proficiency with CI/CD tools, particularly GitHub Actions.
• Deep expertise in AWS cloud architecture and services.
• Demonstrated ability to create and evaluate ERDs and contribute to architectural decisions.
• Strong communication and leadership skills with experience mentoring engineering teams.

Preferred Qualifications:

• Experience with big data technologies such as Apache Spark, Hive, or Kafka.
• Familiarity with containerization tools (e.g., Docker) and orchestration platforms (e.g., Kubernetes).
• Solid understanding of data governance, data quality, and security frameworks.

• Design, implement, and optimize robust data pipelines and ETL/ELT workflows using SQL and Python.
• Lead architecture discussions, including the creation and review of ERDs and overall system design.
• Collaborate closely with Data Engineers, Analysts, and cross-functional engineering teams to meet evolving data needs.
• Build synchronous and asynchronous data APIs for downstream systems to consume the data.
• Deploy and manage infrastructure using Terraform and other Infrastructure-as-Code (IaC) tools.
• Develop and maintain CI/CD pipelines for deploying data applications and services.
• Leverage strong experience in AWS services (e.g., S3, Glue, Lambda, RDS, Lake Formation) to support scalable and secure cloud-based data platforms.
• Handle both batch and real-time data processing effectively.
• Apply best practices in data modeling and support data privacy and data protection initiatives.
• Implement and manage data encryption and hashing techniques to secure sensitive information.
• Ensure adherence to software engineering best practices including version control, automated testing, and deployment standards.
• Lead performance tuning and troubleshooting for data applications and platforms