DescriptionThe Data Platform Engineering Manager will oversee the design, development, and operation of the data platform and the backend services around it - including ETL/ELT and dbt pipelines, workflow orchestration, data-quality and observability practices, and the Python microservices and APIs that serve data and integrate LLM and ML capabilities into production. This role blends people leadership with technical direction: working closely with cross-functional teams, ensuring data integrity and reliability, optimizing platform processes and cost, and mentoring team members. The ideal candidate will have a deep understanding of data platform and backend engineering principles and proven experience managing a team of technical professionals.
Responsibilities:- Leadership: Lead and manage a team of data platform engineers, fostering a culture of innovation, collaboration, and continuous improvement through clear strategy, priorities, and feedback.
- Collaborate: Partner with platform engineers, product teams, stakeholders, and other data teams to shape technical direction and refine data and service designs.
- Team Building: Oversee hiring, onboarding, training, and development initiatives within the data platform team.
- Data Quality & Governance: Establish and enforce data quality, reliability, and observability practices across pipelines (monitoring, lineage, freshness, and validation), ensuring consistency and security.
- Backend & AI/ML Services: Oversee the design and operation of Python microservices and APIs, including those that integrate LLMs and ML models (RAG, embeddings, prompt orchestration, tool/function calling, and agentic workflows), and establish patterns for running LLM/ML-backed features safely, reliably, and cost-effectively in production.
- Data Pipelines & Platform: Oversee the design, development, and maintenance of efficient, scalable data pipelines and ETL/ELT and dbt workflows across source systems, the warehouse, and downstream consumers.
- Define and prioritize data platform projects, aligning with business goals and analytics needs.
- Provide technical guidance, architectural review, mentorship, and career development support for the team.
- Ensure best practices are followed in data engineering, backend development, security, and governance, including CI/CD, deployment automation, schema versioning/migration, and technical documentation.
- Conduct regular performance reviews and provide feedback to team members.
- Ensure seamless integration of data from various sources (CRM, marketing, operational systems) into the centralized data warehouse and downstream services.
- Optimize and enhance data infrastructure and pipelines for improved performance, reliability, and cost-efficiency.
- Review and optimize SQL queries, data models, and service/API performance to ensure efficient and reliable data delivery.
- Champion self-service tools and APIs that enable product teams to independently leverage backend and AI capabilities.
- Help form and oversee data governance and standardization initiatives within the data platform context.
- Partner with IT, product, and analytics teams to drive data-driven decision-making across the organization.
- Stay updated with emerging trends and technologies in data platform engineering, backend systems, and AI/ML to drive innovation.
- Undertake additional assigned duties as requested.
Supervisory Responsibilities:- The Data Platform Engineering team directly reports to the Data Platform Engineer Manager.
- Responsible for hiring, onboarding, performance management, coaching, and career development of direct reports.
Qualifications:- Bachelor's degree in Computer Science, Data/Software Engineering, or a related field (or equivalent experience).
- 6+ years of technical experience in data platform, data, or backend engineering, including SQL, data pipelines, and ETL/ELT processes.
- Expertise in relational databases (MySQL, PostgreSQL), SQL performance optimization, and data warehousing solutions; familiarity with Redis and vector databases (e.g., pgvector, Pinecone, Weaviate) is a plus.
- Proficiency in Python; familiarity with Go and/or TypeScript/JavaScript is a plus.
- Proven experience building and scaling backend services and RESTful APIs, and leading teams that do the same; strong understanding of microservice architecture and distributed systems.
- Practical experience integrating LLMs or ML models into production systems - including several of: prompt engineering, RAG, embeddings/vector search, tool/function calling, evaluation, and cost/latency optimization.
- Strong understanding of data modeling, data integration, governance, and observability best practices (monitoring, logging, tracing), including for AI/ML workloads where applicable.
- Advanced experience with CI/CD pipeline design and hands-on experience with cloud-based data technologies (AWS, Azure, GCP, or similar); container orchestration (Kubernetes) is a plus.
- Experience with Tableau, Sigma, or other data visualization/BI tools is a plus.
- Excellent problem-solving skills with a passion for leveraging data to drive business outcomes.
- Ability to work collaboratively in a fast-paced environment, balancing multiple priorities.
- Spanish speaking bi-lingual candidates are encouraged to apply.
- Candidates may be requested to complete position specific skills assessments.
Working Settings:- Full-time Salaried Exempt, not eligible for overtime.
- Office hours are 8am-5pm, Monday through Friday, Central Time zone, additional hours may be required depending on priorities.
- This position is remote work eligible within the United States. Please be aware: the first week of employment includes mandatory in-person training. Remote start arrangements are not available.
- Also mandatory: One week a year of in-person training with the department.
- Potential for 10% travel, should the need arise.
- Prolonged periods sitting at a desk and working on a computer.
- Must be able to lift up to 15 pounds at times.
Compensation:- The salary varies based on experience and qualifications, but typically ranges from $133,700 to $176,300 per year. Salary paid bi-weekly.
- Monthly Bonus Program - determined by the Company's monthly revenue result and are paid on a "percent to plan" payout formula. (90% = $300, 100% = $600, 110% = $900, 120% = $1,200).
- Monthly phone stipend in accordance with the Company's cell phone policy, currently $120/month.
- Health insurance, Dental insurance, and Vision insurance.
- 401(k) plan with an employer match up to 4% starting the first day of employment.
- Company-paid Life Insurance with options for supplemental coverage.
- Fully paid Short-Term Disability provided by the Company.
- 3 Weeks of PTO annually (details shared during onboarding).
- Employee Stock Purchase Program (ESPP) - Eligible to purchase company stock at a discount after 90 days of employment, with enrollment opportunities each May and November.
