• Inherit, evaluate, and take full ownership of existing ETL/ELT pipelines — identifying what to preserve, improve, or replace based on performance, reliability, and long-term maintainability. • Design and build scalable pipeline improvements or net-new solutions where current practices fall short. • Monitor pipeline health, troubleshoot data quality issues, and proactively resolve performance and reliability problems. • Manage and evolve orchestration tooling with openness to adopting better alternatives as infrastructure needs grow. • Optimize query performance, pipeline efficiency, and resource utilization across Convo’s data environment. • Participate in testing, deployment, and monitoring practices that promote long-term reliability and scalability. • Develop and maintain scalable data transformation processes, schema design, and data models that support evolving business requirements. • Establish and evolve data quality testing frameworks - building practices that catch issues early and create lasting internal trust in our data. • Own data governance, documentation, lineage, version control, and data quality standards across the organization. • Serve as the primary internal resource for data engineering guidance and recommendations, helping set standards and informing data infrastructure decisions across the organization. • Work closely with the data analyst to translate business questions into reliable, queryable data structures. • Educate and guide non-technical stakeholders on how to work effectively with data, what is and isn’t feasible, and how to frame data requests clearly. • Explore and implement tooling to enable self-service data discovery for internal teams, reducing bottlenecks and empowering stakeholders to answer their own questions. • Collaborate with Product, Engineering, Finance, Operations, and Data Science stakeholders to support reporting, forecasting, and business intelligence needs. • Partner with Product and Engineering teams to integrate analytics, event tracking, and reporting into products and platforms. • Establish and document data engineering standards, workflows, and best practices at Convo — building a foundation that is sustainable, well-understood, and not dependent on any single person. • Contribute to improvements in data architecture, tooling, monitoring, automation, and engineering best practices. • Evaluate emerging technologies and tooling to improve efficiency, automation, and accessibility of data systems. • Maintain clear technical documentation and operational standards that support long-term maintainability. • Exercise sound technical judgment in balancing immediate business needs with long-term platform sustainability. • Maintain strong confidentiality and discretion when handling sensitive organizational, financial, operational, and employee data.

• Architect, build, and maintain robust data pipelines • Design and implement analytical data models • Partner with software engineering teams for data ingestion pipelines • Implement validation frameworks and quality checks • Contribute to the evolution of the data platform architecture

• Apply engineering principles and methodologies to solve complex technical challenges • Troubleshoot technical issues and develop effective solutions in a timely manner • Stay up to date with the latest advancements in relevant technologies • Collect, analyze, and interpret large datasets using Excel and other analytical tools • Develop and maintain insightful reports and dashboards to track key performance indicators (KPIs) and identify trends • Use data-driven insights to make recommendations for process improvements, cost reduction, and efficiency gains • Communicate technical information clearly and effectively to both technical and non-technical audiences • Collaborate with cross-functional teams (e.g., sales, marketing, operations) to achieve common goals • Present technical findings and recommendations to management in a concise and persuasive manner • Act as a technical resource and mentor to junior engineers • Understand the business implications of engineering decisions and contribute to strategic planning • Identify opportunities to leverage technology to improve business processes and gain a competitive advantage • Participate in cost-benefit analyses and ROI calculations for engineering projects • Stay informed about industry trends and market dynamics • Develop project plans, track progress, and identify and mitigate risks

Role Description The Manager, Data Engineering role is accountable for the operational excellence, stability, and evolution of the enterprise data platform supporting CenterWell Pharmacy (CWP) and Pharmacy Benefits Management (PBM). This role partners closely with engineering leads and cross-functional stakeholders to prioritize work, ensure platform reliability, and drive continuous improvement of data platform capabilities. Unlike traditional management roles, this position is a hands-on operational leader responsible for executing critical platform accountabilities while also leading and developing a high-performing team. This role focuses on enabling engineering teams to concentrate on software development and innovation by owning operational governance, platform health, financials, and delivery oversight. The Manager, Data Engineering, works within defined enterprise guidelines and processes, applying advanced technical and operational knowledge to solve moderately complex problems. The role receives objectives and determines appropriate approaches, resources, priorities, and execution plans while ensuring alignment with enterprise strategy. This role leads a blended team consisting of approximately 25 to 40 contractors and 3 to 6 associates, with team size fluctuating based on business demand and project needs. Key Responsibilities - Oversee all aspects of data platform operations, including: - SDLC adherence - Change management - Financial governance - Vendor coordination - Cloud cost optimization - Technology lifecycle activities - Collaborate across: - Engineering - Product - Security - Compliance - Business teams Success Profile - Balance of: - Technical depth - Operational rigor - Financial ownership - People leadership - Ability to operate effectively in a fast-paced, highly regulated healthcare environment. Qualifications - Bachelor’s degree in computer science, Information Technology, Engineering, or related field; or equivalent experience - 8+ years of experience in data engineering, software engineering, or enterprise data platform environments - 2+ years of experience leading or managing technical teams, including direct or matrixed reports - Hands-on experience operating and supporting cloud-based data platforms (e.g., Snowflake, Databricks, Azure, or similar technologies) - Strong knowledge of Software Development Life Cycle (SDLC), DevOps practices, and operational readiness disciplines - Experience managing application lifecycle activities, including deployments, documentation, technical debt, and production support - Demonstrated experience managing change control processes using enterprise tools (e.g., ServiceNow or similar systems) - Experience with financial accountability, including budgeting, forecasting, and cloud cost management - Proven ability to manage multiple priorities, projects, and operational demands in a fast-paced environment - Experience working in cross-functional environments, partnering with business and technology stakeholders to align priorities and delivery - Strong communication, leadership, and stakeholder management skills with ability to influence across organizational levels - Demonstrated ability to drive operational excellence, improve system stability, and implement quality improvement practices (e.g., shift-left defect identification) - Experience supporting compliance, security, and risk management practices (e.g., vulnerability management, cyber hygiene, or similar disciplines) Preferred Qualifications - Experience supporting healthcare, pharmacy, or Pharmacy Benefits Management (PBM) domains - Experience operating enterprise data platforms supporting high-volume, near real-time ingestion and analytics workloads - Familiarity with tools and processes such as ServiceNow (SNOW), EAPM, and Technology Lifecycle Management (TLM) - Experience managing vendor relationships, contracting processes, and Statements of Work (SOWs) - Exposure to data governance, data quality, and regulatory requirements (e.g., HIPAA, PCI, or DSCSA) - Experience with cloud cost optimization strategies and FinOps practices - Experience leading or supporting large-scale platform modernization or transformation initiatives - Strong understanding of data engineering frameworks, including ETL/ELT pipelines, data lakes, and data warehouses - Experience implementing monitoring, observability, and production support processes for data platforms - Master’s degree in computer science, Information Technology, Business Administration, or related field - Agile, Scrum, or DevOps certifications Travel While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc. $129,300 - $177,800 per year This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Benefits - Medical, dental and vision benefits - 401(k) retirement savings plan - Time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave) - Short-term and long-term disability - Life insurance - Many other opportunities Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements.