Staff Analytics Engineer

About the position

The Data Team at Babylist powers data-driven decision-making across every aspect of the company’s business. As a product function, we focus on three core aspects of data: engineering, analysis, and data science. We are seeking a Staff Analytics Engineer to take a leadership role in designing, building, and scaling our core data platform and data products. This role is pivotal in driving company-wide data strategy and ensuring our data infrastructure supports impactful, scalable, and future-proof business outcomes. You are a proactive, solution-oriented data leader who thrives on solving complex data challenges. You excel at building scalable data solutions, mentoring others, and driving cross-functional collaboration. You have a track record of influencing strategic decision-making and aligning technical solutions with long-term business priorities. Most of all, you are passionate about leveraging data to create transformative business outcomes. Join us at Babylist to make an impact as part of a team that values collaboration, innovation, and intentional focus.

Responsibilities

• Lead the design and implementation of scalable SQL transformations, frameworks, and governance practices to support data pipelines and models across the organization
• Drive thought leadership to define the team’s dbt strategy through innovations like centralized metric definitions, CI testing frameworks, and organization-wide alignment of data models
• Develop advanced dbt structures like custom macros and metrics layers to enhance flexibility and scalability
• Architect and standardize reusable data models to scale analytics across the company, ensuring alignment with enterprise-wide goals and future scalability
• Define and scale development, quality, and governance standards for Sigma; leading the adoption of advanced features and workflows to maximize efficiency and cross-team alignment
• Collaborate with senior leadership and cross-functional stakeholders to define and execute on data strategies that align with broader company objectives
• Proactively identify and address systemic inefficiencies in workflows and processes, introducing scalable, sustainable improvements across teams
• Mentor and guide team members, junior engineers and data users to develop their skills in advanced techniques, tools, and best practices while fostering a collaborative culture
• Drive innovation in analytics and experimentation, identifying opportunities for advanced methodologies and creating frameworks to scale these efforts across the organization.

Requirements

• 10+ years of hands-on experience in analytics, data engineering, or analytics engineering with demonstrated increasing leadership responsibilities
• Deep proficiency in SQL, including architecting scalable transformations and frameworks to handle enterprise-scale datasets
• Advanced experience with dbt, including designing centralized metrics layers, custom macros, and reusable transformations to standardize data practices company-wide
• Extensive proficiency with Python, including designing reusable frameworks, advanced patterns (e.g., decorators, multithreading), and integrations for data workflows
• Proficiency in Sigma or similar data visualization tools, including the ability to create reusable templates and optimize dashboards
• Experience with cloud-based data warehouses (e.g., Snowflake) and ETL/ELT pipelines
• Proven track record of aligning technical solutions with long-term strategic priorities and communicating technical vision to leadership audiences
• Ability to diagnose complex business challenges and design innovative, scalable solutions that address both short-term and long-term goals
• Demonstrated leadership in cross-functional collaboration, building alignment across diverse teams, and influencing organizational priorities
• Experience mentoring teams and leading initiatives to improve data practices, tooling, and collaboration across the organization.

Nice-to-haves

• Experience with data cataloging and metadata management tools, such as Atlan, Alation, or similar platforms, to drive discoverability, community, and governance of data assets
• Proven ability to lead cross-functional initiatives that improve data quality and reliability, such as implementing data observability frameworks or designing automated data validation processes
• Experience driving cost optimization initiatives in cloud-based data platforms, including warehouse efficiency, query optimization, and storage strategy
• Knowledge of event-driven architectures and tools such as Kafka or AWS SNS/SQS for building scalable, real-time data pipelines
• Experience integrating and scaling third-party tools or platforms to enhance data workflows, such as automation tools, observability platforms, or advanced ETL/ELT solutions.

Benefits

• Company paid medical, dental, and vision insurance
• Generous paid parental leave policy
• 401(k) with company match
• Flexible spending account
• Paid leave (including PTO and parental leave)
• Tools and opportunities to connect with colleagues
• Support for physical, mental and emotional health, parenting, childcare, and financial planning
• Competitive pay and meaningful opportunities for career advancement