Staff Data Engineer

• Serve as core organization mentor and ‘go-to’ thought leader for data engineers, analysts, developers, and others interested in the field
• Be technical owner of end-to-end technical aspects of LTK Data engineering effort including but not limited to LTK Data lake architecture, ETL processes, development and support
• Leverage and utilize suitable technologies to ensure scalability, sustainability, flexibility and security of LTK data platform
• Influence strategic thinking across the team and the broader organization.
• Maintain proof-of-concepts and prototype data solutions, and handles any assessment of data engineering viability and scalability, with data engineering team and in partnership with other departments
• Ensures data solutions include deliverables required to achieve high quality data.
• Present a strong understanding of complex multi-tier, multi-platform systems, and apply principles of metadata, lineage, business definitions, compliance, and data security to project work.
• Mentor and lead peer data engineers in adopting best daa engineering practices
• Work with other departments, assists in building robust systems focusing on long-term and ongoing maintenance and support.

• Experience driving production-grade, multi-million dollar data strategy
• Experience driving end to end ETL data pipelines, from ingestion of data to consumption by business intelligence, analytics and other data consumer teams;
• Experience with Data management and Data governance processes and standards;
• Excellent expertise of system design and application architecture for data platforms;
• Extensive knowledge in SQL fine tuning, optimizers and execution plans;
• Proven experience building complex data models to handle millions of transactions;
• Expertise in Scala, or Python programming at minimum, with demonstrated real-world experience building out data tools in Cloud environments
• 8-12+ years experience in building data pipelines, coding for data management, data warehousing, or other data environments, including, but not limited to Spark. 
• Proven experience with deployment, driving strategy and physical architecture for data engineering,and production at scale
• Profound knowledge of AWS Data services (eg: Redshift, AWS S3, EMR, Glue, RDS, Kinesis, etc.)
• Expert proficiency with: Snowflake, Databricks, Scala, Python and Spark
• Experience in application design and implementation, as senior technical lead role, using agile practices; 
• Experience working on a remote team and coaching / mentoring / leading data engineer team members;
• Bachelor’s degree in information systems, computer science, or a related field; Master’s preferred

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