Role Description The Data Engineer will be part of the Professional Services team, working directly on customer implementations for our B2B sales intelligence platform, helping wholesale distributors get the most out of their data. This is a hands-on role where you'll build data pipelines, configure customer instances, troubleshoot data issues, and collaborate with Customer Success Managers to deliver high-quality solutions. - Data Ingestion & ETL: Build Python/SQL pipelines to ingest invoices, orders, and catalogs. - Perform historical backfills via SFTP/API and manage Airflow DAGs. - Instance Configuration: Set up custom fields, product filtering logic, and sales workflows. - Manage SSO and user provisioning for new rollouts. - AI-Augmented Engineering: Leverage AI coding assistants (Copilot, Cursor) and LLMs to accelerate Python/SQL script generation, data mapping, and debugging. Build ETL pipelines and manage Airflow DAGs. - Customer Communication & Projects: Act as a technical point of contact. Translate complex data issues into clear updates for customers. Own project milestones from kickoff to "Go Live." - Integration & Automation: Build Workato recipes and connect customer ERPs via APIs/webhooks to ensure real-time data flow. - QA & Troubleshooting: Triage HubSpot support tickets, debug data discrepancies in large data sets, and deploy production fixes. - Documentation: Maintain customer data mappings and internal technical runbooks. Qualifications - Bachelor’s degree in Computer Science, Information Technology, or related field (or equivalent experience). - At least 3 years of experience in data engineering, ETL, or related roles. - Strong SQL skills for data analysis and validation. - Proficiency in Python scripting for data processing. - Familiarity with cloud platforms, preferably GCP (e.g., Cloud Storage, Cloud Functions). - Understanding of REST APIs, JSON/CSV data formats, and Git workflows. - Strong communication skills with the ability to explain technical concepts to non-technical stakeholders. Requirements - Experience with workflow orchestration tools (e.g., Apache Airflow). - Familiarity with integration platforms (e.g., Workato, Zapier). - Exposure to CRM tools (e.g., HubSpot, Asana). - Knowledge of eCommerce or sales data models (e.g., products, orders, opportunities). Technical Environment - Data & Analytics: Python, SQL, BigQuery, Looker. - Pipeline & Orchestration: Airflow, GCP (Cloud Storage). - Automation & Integration: Workato, webhooks, APIs. - Infrastructure: GCP, Kubernetes, GitHub Actions. - Systems & Tools: HubSpot, Salesforce, SFTP/FTP, ERP systems. - Project Management: Asana, GitHub. Benefits - Competitive Salary: COP $6,000,000. - Stability: Indefinite contract with all mandatory Colombian legal benefits. - Flexibility: 100% Work From Home (Remote only in Colombia). - Growth: Continuous training, development programs, and clear opportunities for professional advancement. - Culture: A collaborative, supportive, and diverse international team environment.

• Map, extract, cleanse, and transform data (patients, inventory, claims, orders, payers, etc.) • Lead and manage full-cycle data migrations from legacy DME or HME systems into NikoHealth’s platform • Collaborate with implementation consultants and product teams to ensure data accuracy and integrity • Troubleshoot and resolve data discrepancies during migration

Role Description The Data Engineer will support the design, development, and maintenance of data pipelines and data models that power DataSpring's analytics and data platforms. This role focuses on implementing scalable data solutions, ensuring data quality, and collaborating with senior engineers and stakeholders to deliver reliable data for reporting and analysis. This position provides an opportunity to build hands-on experience with Databricks, Azure SQL, and modern data engineering practices while contributing to enterprise data initiatives and discussions. The Data Engineer is a full-time, remote, exempt position and reports to the Sr. Director, Data Engineering & Architecture. Qualifications - 1–3 years of experience in a data engineering or analytics engineering role, including internships or academic projects. - Demonstrated success contributing to data modernization or migration initiatives in cloud environments. - Prior experience working with healthcare or other regulated data environments is highly desirable. - Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field. - Azure Data Engineer Associate or related certification (preferred). - Coursework or certification in AI/ML (preferred but not required). Requirements - Build and maintain ETL/ELT pipelines across Databricks, Azure SQL, and downstream gold-layer models supporting priority projects. - Support development and enhancement of enriched data models, including field-level enrichment logic, recency rules, and provider-level enrichment flags. - Assist in maintaining data logic, including reconciliation between source and target data sources and resolution of duplication and data discrepancies. - Assist in implementing medallion architecture patterns (bronze → gold), ensuring data quality, traceability, and performance at scale. - Support identification and resolution of systemic data quality issues, including null handling, soft deletes, authorization flags, and incorrect organizational mappings. - Support implementation of rules for data in collaboration with product, governance, and engineering stakeholders. - Assist in documenting (Confluence, mapping workbooks) to serve as a single source of truth for enrichment logic and data behavior. - Support collaboration with vendors and partners for vendors providing detailed queries, validation logic, and corrective guidance on upstream data issues. - Collaborate with product owners and engineering teams to ensure data models align with product defined use cases. - Support UAT and release readiness by preparing data, validating counts, and resolving last-mile data defects under tight timelines. Benefits - Competitive compensation and a comprehensive benefits package for full-time employees. - Medical, dental, and vision coverage. - 401(k) with company contributions and matching. - Paid parental leave. - Tuition assistance. - Generous paid time off. - Commitment to investing in our people and supporting professional growth over time. Company Description DataSpring is the trusted data connector at the core of healthcare. For more than 25 years, we have powered the industry with the largest and most complete healthcare data foundation in the U.S., including more than 4.8 million provider data records sourced directly from providers and member data representing 75% of covered lives supplied by health plans. By improving how essential information flows across the system, DataSpring helps healthcare operate more efficiently, accurately, and with greater confidence.

Role Description We are looking to hire two Research and Data Interns to support our work: - Reporting to the Senior Associate focusing on applying data analytics and data science to various challenges in building out systems and sandboxes. - Reporting to the Forest, Land and Agriculture (FLAG) Lead with a focus on data analysis and visualisation, mapping and synthesising relevant frameworks and academic work related to FLAG areas, food systems, and/or the blue economy. These roles would suit someone with strong analytical skills who is keen to apply data analytics and visualisation, data science, Python and SQL to climate-related research questions. You will support the Research team in collecting, structuring, analysing and interpreting climate and sustainability data, with a particular focus on improving the quality, consistency and usefulness of our datasets and analytical outputs. Responsibilities - Support the collection, cleaning, structuring, segmentation, aggregation and documentation of data from sources such as company reports, NGO analytics, disclosure platforms, research papers and sector transition frameworks. - Use SQL to extract, query and organise data from structured datasets, with a clear understanding of data tables, joins, filters, aggregations and how to retrieve the right data for analysis. - Use Python to support data cleaning, transformation, quality checks, exploratory analysis and reproducible workflows. - Contribute to the development of more intentional and robust approaches to data analysis within the Research team, helping to strengthen how data is collected, analysed, interpreted and documented over time. - Conduct research and analysis that helps us understand the state of the corporate climate transition and identify gaps in the wider data ecosystem (for example in Forest, Land and Agriculture (FLAG)) with the ability to understand, synthesise and clearly communicate the core issues, concerns and implications for corporate climate transition analysis. - Support analysis across climate-related themes, including emissions reduction targets, transition planning, sustainable finance, corporate disclosure, and relevant sector-specific issues. - Monitor the integrity, consistency and quality of data, including identifying errors, outliers, gaps and limitations. - Collate, interpret and summarise information from sources such as academic research, industry reports, company disclosures, NGO analysis and climate transition frameworks. - Help to visualise and present key datasets and insights in a clear, accessible and decision-useful way. - Support and maintain administrative systems and processes developed within the Research and Program team, for example project management systems such as Asana. - Provide ad-hoc support to the delivery of key milestones and projects, as required. Qualifications - You are pursuing, or have recently completed, a degree in a sustainability, data, finance, economics, environmental science, computer science or related field, or you have relevant equivalent experience. - Strong interest in applying data analytics and data science to climate, sustainability and finance-related research questions. - Knowledge of SQL, including the ability to query datasets, filter and aggregate data, use joins, understand table structures, and explain clearly how you extracted and prepared data for analysis. - Knowledge of Python, particularly for data cleaning, transformation, exploratory analysis, visualisation, quality checks and working with datasets. Experience using packages such as pandas, NumPy, Jupyter notebooks or similar tools would be beneficial. - Good understanding of analytical fundamentals, including data quality, reproducibility, documentation, assumptions, limitations and interpretation of results. - Good understanding of climate-related data, ESG and disclosure frameworks such as TCFD. - Good understanding of issues in climate change reporting, sustainable finance and companies’ emissions reduction targets. - Familiarity with Forest, Land and Agriculture, known as FLAG, food systems, and/or the blue economy and related areas including nature and biodiversity is desirable for one of the positions. - Proficient user of the MS Office suite, particularly Excel. - High attention to detail with a vigilant approach to research and data analysis. - Strong time management skills, maintaining high levels of attention to detail, speed and a well-organised workflow. - Collaborative approach, creating a positive working atmosphere and supporting each other. - Excellent written and verbal communication skills, including fluency in English. - Access to a personal computer with adequate security provisions. Requirements - Your availability: Full time ideally. We are looking for candidates to start in July 2026, for a period of 6 months. - Reports to: Senior Associate (Research & Program) or Forest Land and Agriculture Lead (Research & Program). - Application deadline: Please apply by 5pm on Friday 19th June. Benefits - The opportunity to contribute to and have a lasting impact on the transition to a sustainable, low-carbon economy. - Opportunity to work at the intersection of climate, finance, research and data science, a critical area for climate action. - The chance to build practical experience using Python, SQL and data analysis in a mission-driven research environment. - An adaptive company culture and the chance to work closely with an entrepreneurial and diverse team. - Exposure to the opportunities and challenges of working in a start-up environment. - Compensation: £17 per hour, or local market equivalent if based outside the UK.