• Create, configure, and maintain robust Data Migration workflows, dataflows, and data mappings to integrate data between SAP (ECC, S/4HANA, BW) and non-SAP systems • Analyze business requirements to design and develop source-to-target mappings with transformation logic • Perform in-depth analysis of large and complex datasets from multiple sources to identify data anomalies, quality issues, and actionable insights • Develop complex transformation logic including data cleansing and standardization routines and business rule implementation and validation • Develop data profiling and assessment routines to analyze data patterns and distributions and identify data quality issues and anomalies • Execute full life cycle conversions, including mock data loads, reconciliation, and managing cutover activities • Configure and integrate diverse sources including flat files, web services, APIs, cloud platforms, and non-SAP enterprise applications

• Partner with business owners to cultivate a shared vision for the problem space, constraints, priorities and ideal end state, and be able to articulate and advocate for this perspective. • Lead the full lifecycle of ML and LLM platform workstreams; from data ingestion, training, and deployment to the ongoing optimization of live user workflows based on performance metrics and feedback • Work with internal teams and end users to develop a deep understanding of requirements, perform thoughtful solution design, use data to test hypotheses, and support teams throughout execution. • Write detailed user stories for new features, capturing detailed descriptions of business rationale, requirements, and success criteria that are defined by measurable outcomes. • Develop short- and long-term roadmaps that deliver maximum value with minimum risk and assume ongoing iteration. • Partner with AI Researchers to mature proofs-of-concept into production-ready capabilities. • Perform hands-on exploration of user feedback, healthcare records and validation data to validate model performance.

Pelago is the world’s leading virtual clinic for Substance Use Management. Our program provides guidance, support and treatment for members seeking to overcome their tobacco, alcohol and opioid use. From unhealthy habits to active substance use disorders, Pelago delivers a personalized solution based on individual health, habits, genetics, and goals, providing care for members wherever they might be on the substance use spectrum. Pelago's suite of virtual services ranges from education, to cognitive behavioral therapy (CBT) to comprehensive medication-assisted treatment (MAT). Pelago enables employers and health plans to deliver accessible, affordable, and effective treatment for substance misuse. Pelago has scaled to helping hundreds of employers and health plans and has already helped more than 750,000 members manage their substance use better. We have recently closed our Series C and raised over $151m from leading global investors. If you are passionate about making an impact on the health of others, join us and make it happen! About Pelago Data: Our Data team sits at the center of how Pelago makes decisions. As we scale, we’re evolving our data function to bridge the gap between raw data and real business insight. We transform complex healthcare and product data into clean, reliable, and well-documented models that power reporting, experimentation, AI initiatives, and day-to-day decision-making across the company. Overview of the Role: We’re looking for an Analytics Engineer who loves building scalable data models, thinking deeply about business logic, and creating reusable data assets. In this role, you’ll help shape how data is structured and defined across Pelago—ensuring consistency, quality, and usability for everything from dashboards to experimentation to future machine learning use cases. What You’ll Do: Build the foundation for analytics - Design, build, and maintain scalable dbt models for analytics and reporting - Develop modular, well-documented transformation logic in Redshift - Optimize performance and maintainability of transformation pipelines - Implement testing, validation, and observability standards to ensure data quality Own business logic and metrics - Translate ambiguous business requirements into structured, reusable data models - Define and maintain standardized KPIs and metric logic - Own and evolve Pelago’s semantic layer to ensure consistency across teams - Build reusable data marts for dashboards, experimentation, ROI analysis, and AI workflows - Reduce metric inconsistencies and reporting fragmentation Partner across the business - Work closely with Data Engineering to ensure reliable upstream pipelines - Collaborate with Product, Clinical, Client Success, Finance, and Growth teams - Support Data Analysts with clean, analysis-ready datasets - Contribute to documentation, data governance, and analytics best practices Enable advanced analytics - Structure data for experimentation, personalization, ROI measurement, and AI initiatives - Prepare datasets for downstream data science and machine learning workflows - Identify opportunities to improve analytics velocity through better modeling and abstraction What We Look For: Required - 3+ years of experience in analytics engineering, data analytics, or data modeling - Advanced SQL skills and experience building production-grade data models - Strong understanding of data warehousing concepts and dimensional modeling - Experience with dbt and analytics engineering best practices - Experience working in a modern data stack (Redshift, Snowflake, or similar) - Proven ability to translate business needs into scalable data solutions - Experience working in cross-functional, agile environments Preferred - Experience with Looker or similar BI tools and semantic layer design - Familiarity with healthcare data or regulated environments - Experience supporting experimentation, ROI measurement, or product analytics - Exposure to AI/ML data preparation or feature-ready modeling - Experience implementing data quality testing and observability frameworks What You'll Love About Us: We have a whole host of perks for our people! From life essentials to nice-to-haves, there are more than a few good reasons to love working with us. We strive to ensure Pelago employees have equitable access to healthcare, wellbeing, time away, and then some. - Generous and meaningful equity package - Private Health Coverage - Pension Plan - Unlimited PTO Policy, Bank Holidays, & company wide “Me Time Days” - Paid maternity, paternity, & new parent leave - Flexible working environment - Annual Learning and Development stipend to support continued learning and career development - Wellness Reimbursement Program - Access to Reproductive & Family Planning Care - Substance Use Support for employees and family members At this time, we are unable to offer visa sponsorship for this position. Before you apply, see how we build. We write about our technical decisions, product philosophy, and the real challenges of scaling behavioral health. Read the blog → https://pelagohealth.ai/ The provided range reflects our US target salary range for this full-time position, which is part of our broader total compensation package, including incentive bonus program, stock options, comprehensive benefits, and incentive pay applicable to eligible roles. Individual pay within the range will vary based on a variety of factors like role-related experience and education, internal pay equity, and other relevant business factors. At Pelago, we are committed to an equitable and fair pay philosophy and review total compensation for our employees at least twice a year. Base Pay Range $150,000—$160,000 USD

We are K1x. Our platform powers the first fully digital K-1, transforming how alternative investment tax data is extracted, validated, distributed, and analyzed. Trusted by leading institutional investors, fund administrators, and accounting firms, K1x replaces manual, error-prone workflows with scalable, intelligent software. k1x.io   As our platform evolves toward deeper analytics, insights, and AI-driven capabilities, data engineering is becoming a foundational pillar of our product and technology strategy.  About The Role We are seeking a Data Engineer to design, build, and maintain the data pipelines and infrastructure that power K1x’s machine learning initiatives and future analytics-driven product features.    This role sits at the intersection of Product Engineering, Data, and Machine Learning. You will be responsible for creating reliable, scalable, and high-quality data systems that enable downstream ML models, reporting, and embedded analytics.  What You’ll Do  - Design, build, and maintain scalable data architectures supporting operational, analytical, and ML workloads.  - Contribute to the evolution of K1x’s data lakehouse strategy, including adoption of Snowflake.  - Develop and maintain robust ETL/ELT pipelines for large-scale data processing.  - Implement data quality checks, validation, and monitoring.  - Enable machine learning workflows with clean, well-structured datasets.  - Support analytics and reporting use cases including Power BI.  - Partner with Product, Engineering, and AI teams on data solutions.