We're in search of a seasoned Senior Data Engineer to join our dynamic team, taking on a pivotal role in crafting and refining data systems that power our business intelligence and analytics endeavors. In this role, you'll be instrumental in designing, building, and maintaining scalable data pipelines and architectures, leveraging tools like Python, AWS Glue, and Airflow. The ideal candidate will excel in managing a variety of data formats such as CSV, XML, JSON, and Parquets, seamlessly integrating them into our SaaS database and Redshift for efficient data extraction to fuel BI tools. As a Senior Data Engineer, you'll participate in all facets of development, from conception to implementation, with opportunities to mentor junior members of the team.

Roles and Responsibilities:

• Design and develop scalable, high-performance data architectures to support enterprise-level analytics and business intelligence requirements.
• Define comprehensive strategies for data storage, movement, and governance across diverse formats, including CSV, XML, PDF, JSON, Parquets, and dataframes.
• Architect solutions that seamlessly integrate with AWS services, with a focus on leveraging AWS Glue for ETL processes and Amazon Redshift for data warehousing.
• Evaluate and implement cutting-edge database technologies and tools to ensure our architecture remains innovative and cost-efficient.
• Collaborate closely with ETL developers, data engineers, and BI developers to establish a cohesive workflow from data ingestion to insight generation.
• Establish and enforce data governance and quality standards, guaranteeing data accuracy, accessibility, and compliance with security and privacy regulations.
• Spearhead initiatives to enhance database and data pipeline scalability, performance, and resilience.
• Provide architectural guidance and technical leadership to the development team, supporting them through the implementation phase.

Required Skills/Experience:

• Minimum of five years of experience in a senior data engineering capacity.
• Proficiency in Python, AWS Glue, Airflow, and the construction of data pipelines.
• Experience with FastAPIs, Spark, ML/AI pipelines, Athena, Redshift, PySpark, and Snowflake.
• Strong expertise in DataOps, data parsing, and the deployment of high-scale data models.
• Demonstrated proficiency in data visualization and reporting tools.
• Exceptional analytical and problem-solving capabilities.
• Proven ability to thrive in fast-paced environments, managing multiple tasks with efficiency.
• Excellent communication and collaboration skills, with a track record of driving data-centric solutions across departments.