Job Closed
This listing is no longer active.
Lean Tech is a rapidly expanding organization situated in Medellín, Colombia. We pride ourselves on possessing one of the most influential networks within software development and IT services for the entertainment, financial, and logistics sectors. Our corporate projections offer many opportunities for professionals to elevate their careers and experience substantial growth. Joining our team means engaging with expansive engineering teams across Latin America and the United States, contributing to cutting-edge developments in multiple industries.
Senior Analytics Engineer
Location
Latin America (LATAM)
Posted
33 days ago
Salary
0
Seniority
Senior
Job Description
Senior Analytics Engineer
Lean Solutions Group
Role Description We are seeking a highly motivated Analytics Engineer to join our growing Data & Insights organization. In this role, you will partner closely with the Associate Director of Data Insights to build a curated semantic and reporting layer that serves as the trusted foundation for all business intelligence, reporting, and analytics solutions across internal teams and client-facing products. This role blends deep technical rigor with execution speed, ideal for someone who takes pride in building well-modeled, secure, and performant data foundations while also delivering analytics products that create immediate business value. You will work hands-on with modern embedded and enterprise BI tools, including Bold BI and Reveal BI, alongside cloud data platforms to deliver scalable, governed, and reusable analytics experiences. Qualifications - Semantic & Reporting Layer Development: Design and maintain a curated semantic layer that standardizes business metrics, definitions, and hierarchies ensuring consistent, governed, and reusable data access across all BI and analytics consumers. - Data Modeling: Build and optimize robust dimensional and analytical data models (star/snowflake schemas, aggregated layers) that support performant, scalable reporting across diverse use cases. - Performance Tuning: Identify and resolve query performance bottlenecks through indexing strategies, materialized views, query optimization, caching configurations, and push-down SQL techniques. - Security Implementation: Implement and enforce row-level security (RLS), role-based access control (RBAC), and data masking policies within the semantic layer and BI platforms to ensure data is accessed only by authorized users. - Collaboration: Partner with Product, Data Engineering, and Client Success teams to translate business requirements into production-ready data models and analytics deliverables. - Data Quality & Validation: Perform exploratory data analysis and validation to ensure accuracy, consistency, and trust in all published metrics and insights. - Documentation: Document semantic layer definitions, data models, security policies, and implementation patterns to support adoption, auditability, and long-term maintainability. - Dashboard & Report Development: Design and deliver dashboards, KPI scorecards, and embedded analytics using Bold BI, Reveal BI, and other enterprise BI tools, with a strong emphasis on speed to value and stakeholder adoption. Requirements - A well-structured, governed semantic layer serves as the single source of truth for all reporting and analytics consumers. - Data models are clean, performant, and extensible — reducing ad hoc rework and enabling faster future delivery. - Security policies are consistently enforced at the data layer, ensuring compliance and appropriate data access across user roles. - Dashboards and reports built in Bold BI and Reveal BI are scalable, reusable, and trusted by stakeholders. - Time-to-delivery decreases through standardization, reusable models, and template-driven builds. Soft Skills - Exceptional Communication: Articulate complex analytical insights and data-driven narratives effectively to both technical and non-technical stakeholders, including the creation of clear Standard Operating Procedures (SOPs). - Proactive Ownership: Demonstrate initiative by leading the adoption of new processes and independently managing small-scale system enhancement projects from conception to completion. - Analytical Problem-Solving: Employ a systematic approach to interpret data trends, troubleshoot reporting and visualization issues, and recommend pragmatic, effective process improvements. - Meticulous Attention to Detail: Uphold the highest standards of data quality and report accuracy through rigorous validation and a detail-oriented approach to all deliverables. - Stakeholder Engagement: Collaborate effectively with cross-functional teams, including Product and Data Engineering, to understand user pain points and translate business requirements into technical solutions. - Facilitation and Mentorship: Confidently facilitate virtual training sessions and host technical office hours to support user adoption and enhance data literacy across the organization. Benefits - Join a powerful tech workforce and help us change the world through technology. - Professional development opportunities with international customers. - Collaborative work environment. - Career path and mentorship programs that will lead to new levels.
Related Guides
Related Categories
Related Job Pages
More Analytics Engineer Jobs
Data Engineer – GTM, Analytics
SardineCombine risk, compliance, and payment protection to increase customer trust and loyalty - all from one powerful API.
• Build and own Sardine’s internal data infrastructure, integrating CRM, marketing, product, finance, and operational systems into a cohesive, well-modeled data warehouse. • Own the data warehouse partitioning strategy, access controls, and security architecture in close partnership with the Security and Infrastructure teams to meet compliance and performance requirements. • Take full ownership of billing data infrastructure, including backend warehouse tables, data models, and ongoing maintenance. • Design, implement, and own ETL/ELT pipelines to pull and merge data from multiple internal and external systems, ensuring clean, reliable, and scalable data flows across the organization. • Partner with data science, engineering, revenue operations, and executive stakeholders to define and track KPIs, ensuring business decisions are grounded in data. • Serve as the connective tissue between Revenue Operations, Business Operations, and Product/Eng, translating complex requirements into elegant data solutions. • Champion data quality and governance, ensuring insights are consistent, trustworthy, and well-documented. • Build dashboards and analytics that provide key insights for executive leadership, GTM, product, and finance teams. • Analyze data to identify the best ways to deliver value to clients and inform product decisions.
Senior Analytics Engineer
LandingLanding is reinventing renting with flexible-lease apartments for people who want to say hello to possibility.
• Own Landing's dbt models, data pipelines, and warehouse architecture. • Maintain dbt model library — keeping models clean, tested, documented, and aligned with business data usage. • Manage Landing's ELT stack — including Stitch, Snowflake, dbt, and associated monitoring and orchestration tooling. • Establish a finance and operations data spine — authoritative source of truth for core executive KPIs, metric definitions, and warehouse logic. • Develop analytics engineering standards, tooling decisions, and long-term roadmap for data platform. • Foster cross-functional data partnerships with Engineering, FP&A, and Accounting — translate between technical infrastructure and business need. • Enforce data quality standards, testing frameworks, and metric governance practices. • Support executive, board, and investor reporting — work directly impacts high-stakes decision-making and fundraising.
Digital Analytics Tag Management Engineer
Booth and Partners Pte LtdOpenLoop was co-founded by CEO, Dr. Jon Lensing, and COO, Christian Williams, with the vision to bring healing anywhere. Our telehealth support solutions are thoughtfully designed to streamline and simplify go-to-market care delivery for companies offering meaningful virtual support to patients across an expansive array of specialties, in all 50 states. We have a relatively flat organizational structure here at OpenLoop. Everyone is encouraged to bring ideas to the table and make things happen. This fits in well with our core values of Autonomy, Competence and Belonging. We want everyone to feel empowered and supported to do their best work. We’re based out of Des Moines, Iowa, but we’ve got teammates spread across the US in many departments. Day to day, we collaborate most frequently using Slack, Notion, Linear, Figma, FullStory, and Zoom.
Role Description To have a material strategic and financial impact on our clients, we need to have an Analytics Engineering team able to consistently do the best work of their careers for each client. The environment is complex: a multi-platform stack spanning GTM, GA4 360, Quantum Metric, Dynamic Yield, performance marketing pixels, CRM tracking, server-side event pipelines, and a headless Shopify architecture. The right candidates will be technically strong, comfortable with ambiguity, and able to collaborate closely with product and engineering teams to unblock implementation and drive tracking quality at pace. - Tag Implementation & Backlog Clearance: Day-to-day implementation, QA, and documentation of tags across GTM, GA4, Quantum Metric, Dynamic Yield, performance marketing pixels (Meta, Google), CRM, and server-side event pipelines. Clear and manage an active backlog with a focus on speed and accuracy. - Figma-to-Data-Layer Scoping: Translate new feature designs into detailed data layer specifications, defining parameters, values, and formats for developers. Own the tracking scope from Figma through to QA sign-off. - Developer Collaboration: Work closely with product and engineering teams to unblock data layer implementation, reduce friction during dev cycles, and ensure tracking fires correctly across releases without breaking downstream platforms. - Cross-Platform Sessionization & Attribution: Support and maintain tracking consistency across web, native app (Flutter), and Shopify checkout, including custom app sessionization logic, UTM persistence, and attribution integrity. - Performance Marketing Pixel Integrity: Monitor and protect Meta and Google pixel event scores, which directly inform ad spend optimization across hundreds of millions in media budget. Prioritize critical pixel fixes above internal data issues. - Server-Side Tracking: Maintain client-side and server-side event sync via the LR platform, ensuring consistent 200-return rates and parity between client and server event pipelines. - A/B Testing Infrastructure Support: Maintain DY-to-QM event piping (dyrc, dy2qm), variant tracking events, and feature flag reporting to support experimentation velocity. - Monthly Data Audits: Participate in monthly data audits comparing GA4 events against the source of truth. Triage breaks between GTM hot-fixes and developer ticket resolution, and document findings. - Consent Management Compliance: Support OneTrust → GTM consent enforcement following strict change management protocols involving security and legal stakeholders. - QA Framework Development: Contribute to an emerging agentic QA framework using AI-assisted assertion testing against BigQuery downstream data. - Intake & Refinement Participation: Join weekly refinement meetings to assess incoming epics and tickets for data tracking impact, applying domain analytics labels and scoping new tracking requirements. - Solution Design Document (SDD) Maintenance: Contribute to and maintain the centralized SDD, the shared source of truth across engineering, product, and analytics used to govern all tracking. Qualifications - Tag Management Experience: 3–5+ years of hands-on tag management in a DTC or e-commerce environment. - Google Tag Manager (GTM): Strong proficiency in GTM, including implementation, governance, consent enforcement (OneTrust to GTM), hot-fix process, and tag structure best practices. - GA4: Solid experience with GA4 including custom dimension governance, event schema management, and intentional reuse of dimensions to control BigQuery event volume and downstream data quality. - Performance Marketing Pixel QA: Demonstrated ability to QA Meta CAPI and Google Ads event scores and understand how data layer accuracy directly impacts ad optimization. - Figma-to-Data-Layer Translation: Ability to scope tracking requirements from Figma designs into developer-ready data layer documentation, technically fluent enough to collaborate with engineers and connect to business outcomes. - Cross-Platform Tracking: Experience maintaining tracking consistency across web, native mobile app, and Shopify checkout, including sessionization, attribution, and server-side/client-side parity. - Shopify Data Layers: Familiarity with Shopify data layer constraints, checkout instrumentation limitations, and nuances like automated discounts, compared price fields, and Shop Pay redirect behavior. - Developer Collaboration: Proven ability to work alongside engineering teams, unblock data layer implementation issues, and scope tracking tickets clearly in Jira. - Documentation: Strong documentation habits with experience maintaining centralized, cross-functional tracking documentation. Requirements - Bachelor’s degree in Computer Science, Software Engineering, or a related field. - Server-Side Tracking Platforms: Experience with platforms like LR (Elevar) or similar for managing client/server-side sync and 200-return rate monitoring. - BigQuery: Experience with BigQuery event volume management and downstream pipeline health monitoring. - Headless Site Architecture: Familiarity with headless/server-side rendered environments and client-side event capture patterns. - App Tracking: Experience with native app tracking (Flutter or similar), including custom sessionization logic and web/app event parity approaches. - Agentic QA: Interest in or experience with AI-assisted QA frameworks (e.g., Claude, ChatGPT, or Gemini) for automated assertion testing against analytics data. - Comfort working in a fast-paced, backlog-driven embedded team environment with multiple stakeholders across analytics, product, engineering, and legal. - Solid coding foundation. You can collaborate with internal and external SMEs to problem solve and create smart solutions. - Expectations Wizard. You always under-promise and over-deliver. - Agile. You have an innate ability to embrace change and quickly adapt to new situations, changes in direction and competing priorities within a results-driven environment. You know how to learn fast with the goal of operating independently without sacrificing a quality output. - Proactive. You are experienced at identifying risks & resolving issues, escalating as needed to senior leadership across an entire portfolio of client projects. - Live in the details. Solid problem-solving skills with a high attention to the little things. You bring clarity to chaos. - Are confident, yet kind and low on ego. 'Nuff said. - Wear many hats. Demonstrated ability to manage multiple, simultaneous projects and manage programs. - Well rounded. Have experience with various digital projects. - 1+ years of experience working in an agency or client-facing environment. - Prior experience in DTC, fashion, or high-growth e-commerce strongly preferred. - TPM-adjacent skills: Ability to manage intake, scope tickets, and facilitate cross-functional tracking discussions without formal project management authority. Benefits - Full-time position - Work from Home - Prepaid Medicine: Your health is our priority! - Life Insurance: Peace of mind for you and your loved ones! - Indefinite-Term Labor Contract: Stability and all legal benefits included!
Senior Analytics Engineer
Lyra HealthTransforming behavioral health through technology with a human touch
• Report to the team lead and be a key contributor to our migration from a legacy SQL Server data stack to a modern cloud data stack consisting of Snowflake, dbt and Tableau**• Design and build data pipelines using Snowpark and/or Snowpipe where native connectors do not exist for Snowflake for various data sources**• Contribute to designing and building a new multi-dimensional data model in Snowflake**• Work closely with our Business Intelligence team - monitoring and implementing enhancement requests for the data warehouse to meet the reporting demands of stakeholders The successful candidate will also be given the opportunity to develop mentoring skills as we look to expand the team’s skillset to match those of our counterpart US team. As we work collaboratively with team members in different timezones, it is important that the candidate has strong interpersonal skills.


