Senior Engineering Manager, Data Pipelines

TetraScience is the Scientific Data Cloud company with a mission to accelerate scientific discovery and improve and extend human life. The Scientific Data Cloud is the only open, cloud-native platform purpose-built for science that connects lab instruments, informatics software, and data apps across the biopharma value chain and delivers the foundation of harmonized, actionable scientific data necessary to transform raw data into accelerated and improved scientific outcomes. Through the Tetra Partner Network, market-leading vendors access the power of our cloud to help customers maximize the value of their data.

Our core values are designed to guide our behaviors, actions, and decisions such that we operate as one. We are looking to add individuals to our team that demonstrate the following values:

• Transparency and Context- We trust our people will make the right decisions and overcome any challenges when given data and context.
• Trust and Collaboration- We believe there can only be trust when there is transparency. We are committed to always communicating openly and honestly.
• Fearlessness and Resilience- We proactively run toward challenges of all types. We embrace uncertainty and we take calculated risks.
• Alignment with Customers- We are completely committed to ensuring our customers and partners achieve their missions and treat them with respect and humility.
• Commitment to Craft- We are passionate missionaries. We sweat the details, as the small things enable the big things.
• Equality of Opportunity- We seek out the best of the best regardless of gender, ethnicity, race, or age. We seek out those who embody our common values but bring unique and invaluable perspectives, talents and advantages.

What You Will Do

1. Strategy:
   • Collaborate with cross-functional teams, including Product, Data Architects, and Solutions Architects, to define the strategic direction for the data pipeline team.
   • Ensure alignment of the data pipeline strategy with the company's broader goals and objectives.
2. Team Organization & Leadership:
   • Lead, mentor, and grow the engineering team, ensuring cross-team alignment to deliver on the company's objectives.
   • Foster a culture of collaboration, innovation, and continuous improvement within the team.
   • Invest in the professional development of team members, providing opportunities for training, mentorship, and career growth.
   • Act as the primary point of contact for the data pipeline team, communicating with other departments, stakeholders, and senior management.
   • Ensure that all stakeholders are informed and aligned on the team's priorities, challenges, and achievements.
3. Project Tracking & Management:
   • Oversee the planning, execution, and delivery of projects.
   • Continuously improve agile practices to streamline processes and enhance team productivity.
   • Work closely with Product Managers to understand product requirements and translate them into technical specifications and roadmaps.
4. Quality Assurance:
   • Establish and enforce quality standards, ensuring data accuracy, reliability, and scalability.
   • Promote a culture of testing and validation, ensuring high-quality and error-free features before user acceptance testing.
   • Ensure that the team adheres to data governance policies and complies with relevant regulations and standards.
5. Reporting & Measurable Outcomes:
   • Define and track key performance indicators (KPIs) for the data pipeline team, ensuring transparency and accountability.
   • Regularly report on the team's progress, challenges, and achievements to senior leadership and stakeholders.
6. Technical Oversight:
   • Stay updated with the latest trends and technologies in data engineering, ensuring that the team adopts relevant tools and practices.
   • Actively participate in technical designs and provide technical guidance and oversight, ensuring that the team's solutions are scalable, maintainable, and aligned with industry best practices.

Requirements

• BS/MS in engineering, 7-10 years of management experience
• Experience in building or leading data integration and / or data platforms
• Previously a senior individual contributor and hands on experience in architecture and implementation
• People management and project management skills
• Experience using AWS (EC2, S3, CloudWatch, Lambda, SQS, etc.)
• Leadership, team building, and mentoring skills
• Strong communication, interpersonal, and confl