• Salary in the $190-215,000
• plus Bonus
• Comprehensive Benefit and Retirement Programs. 
• Partially Remote - You will work on-site for three days in their CT location, and then remotely on Mondays and Fridays.
• long-time client 
• Tremendous opportunity to work for one of the most successful, stable and growing global Financial firms.

Our client has been at the forefront of the Fintech space for almost five decades. They quite literally invented the first electronic trading-floor technology.  With that said, they take tremendous pride in being primarily a technology company. 

As Senior Data Architect – Team Lead, you will collaborate with the enterprise architect to develop a program, run as process owner, and build, and configure acquire tooling to design solutions with performance, maintainability, scalability, and reliability in mind. The ideal candidate will have demonstrated leadership skills with the ability to mentor, influence, and partner with engineering teams to deliver scalable robust solutions.

• Development of patterns, standards and best practices in the data engineering and solutions space
• Data architecture strategy, design and best practices data platforms and related solutions.
• Review and identify data solutions in collaboration with the technology teams across the enterprise
• Work with engineering teams to implement architectures
• Influence product and delivery requirements, roadmaps, and vision
• Manage data engineering team under the Enterprise Architecture organization
• Deliver enterprise solutions / architectures with emphasis on data privacy, integrity, scalability, and availability
• Produce organized and comprehensive system architectures and the related documentation
• Design and build functioning proof of concepts for proposed architectures

• 7+ years of hands-on cloud engineering experience with public clouds (AWS required)
• 5+ years of experience of Data Lake platform implementation and Terraform
• 3+ years of IT project/team management experience

Working experience with:

• Building and leading engineering teams
• Designing, building, and running enterprise distributed systems, real-time ETL, data pipelines
• AWS services such as Athena, Glue, Lambda, S3, DynamoDB, NoSQL, Relational Database Service (RDS), Amazon EMR and Amazon Redshift
• RDBMS, Spark, Hadoop, Kafka
• Programming languages such as Java and Python
• CI/CD pipelines and infrastructure as code (IaC)
• Serverless big data solutions in AWS