Role Description As a Senior AI Data Engineer, you will build the data foundation that powers reporting, operational decision-making, automation, and AI across the company. You will design and deploy a modern AWS-based lakehouse architecture from the ground up, shaping how data is collected, governed, and delivered. Working across Engineering, Product, Finance, and Business Operations, you will establish the platform, standards, and engineering practices that transform data into a trusted enterprise capability. You'll make an impact by: - Building a modern, scalable enterprise data platform that supports analytics, business intelligence, and AI. - Creating trusted, governed data products that become the foundation for enterprise reporting and decision-making. - Designing reliable, automated data pipelines that integrate our core business systems into a single, scalable architecture. - Establishing engineering standards for data quality, governance, security, observability, and platform reliability. - Partnering with business and technology leaders to solve complex data challenges and enable new capabilities across the organization. - Helping define the long-term vision and technical direction of Sangoma's enterprise data platform. Qualifications - Experience building modern cloud-based data platforms. - Comfortable working across engineering, product, and business teams. - Experience with cloud data platforms in AWS or a similar cloud environment. - Building data pipelines using Python and SQL. - Data modeling, transformation, and orchestration tools. - Modern data warehouses such as Snowflake, Redshift, or equivalent platforms. - Git-based source control and CI/CD development practices. - Designing reliable, secure, and well-governed data solutions. Requirements - Experience in one or more of the following is a plus: - Snowflake or other cloud data platforms. - AI and machine learning data pipelines. - ERP and CRM platforms such as NetSuite and Salesforce. - Search and vector database technologies. Benefits - Extended Healthcare Plan (Medical, Disability, Dental & Vision). - RPP - Group RRSP. - Group Life - AD&D - Critical Illness Insurance. - Paid Time Off Benefits. - Work From Home - Flexible hours. - Entrepreneurial work environment partnered with high growth career opportunities.

Role Description As a Data Science Intern, you will support ongoing research initiatives that keep our enterprise products and our clients' hiring processes on the absolute cutting edge and leverage machine learning to shape the future of hiring. Partnering closely with our world-class data scientists and cross-functional partners in Product Science and Product and Technology, you will have the opportunity to build, validate, and scale machine learning models and agentic workflows. You will also conduct applied research on systems and processes to continuously advance our natural language processing (NLP) and ethical AI capabilities. Essential Duties and Responsibilities - Applied Research & Modeling - Support ongoing research initiatives that keep us on the cutting edge, including in agentic workflow development. - Work with machine learning models to build products and conduct research. - Write code to develop prototypes and utilities to extend or improve our product suite. - Data Preparation & Quality - Drive the preparation of data used to train deep learning models and score unstructured data. - Assure quality of our software in terms of content, scoring, and functionality. - Performance modeling and data analysis. Qualifications - Required - Bachelor’s degree required, with a Master’s degree or PhD in progress in a quantitative/programming field (Computer Science, Statistics, Mathematics, Engineering, Psychology, Economics, Data Science, or related). - Understanding of statistics, machine learning, and deep learning fundamentals. - Proficiency in Python, including common ML libraries (e.g., numpy, pandas, scikit-learn). - Experience with version control (e.g., Git). - Ability to analyze large datasets and draw meaningful, actionable insights. - Strong problem-solving skills — able to synthesize information from multiple sources to solve problems. - Team player with strong collaboration and communication skills; comfortable working closely with data scientists, engineers, and I/O Psychologists. - Self-motivated and able to work effectively with limited supervision; strong prioritization skills. - Preferred - Awareness of state of the art methods in machine learning, deep learning, NLP, and/or generative AI. - Exposure to large language models (LLMs) and generative AI (e.g., prompt engineering, fine-tuning, agentic design patterns, agentic evaluation methods). - Familiarity with SQL and database querying. - Familiarity with cloud platforms (AWS preferred) for ML workflows. Additional Information - All team members at Hirevue are expected to embody our core values, which are the H.E.A.R.T. of Hirevue: - Hero for our Customers - Enjoy the Journey - Always do the Right Thing - Reach Forwards - Take Action and Go - Hirevue takes security seriously and has measures in place to protect work-related data in a remote setting. - Our organization has implemented a BYOD (Bring Your Own Device) policy, ensuring personal apps and data are kept separate from work apps and data. - Hirevue is committed to equal treatment and opportunity in all aspects of recruitment, selection, and employment. - All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other category protected under the law. - Hirevue is NOT currently hiring in: AK, HI, IA, ME, MS, NM or WV.

Role Description The Data Engineer designs, builds, and operates reliable, scalable data pipelines on PowerSecure’s Azure data platform to enable trusted analytics and self‑service BI. This role partners with BI Developers, the Data Architect, and business stakeholders to ingest, model, and deliver high‑quality data using Azure Data Factory, Databricks (PySpark/Spark SQL), and Delta Lake (including Delta Live Tables). Responsibilities include: - Batch/stream ingestion - Data transformation (ELT) - Orchestration - Data quality enforcement - Operational support Qualifications - 2+ years of hands‑on data engineering (or comparable software engineering with significant data work) - 2+ years building pipelines on Azure and Databricks (or equivalent cloud + Spark) - Strong SQL (analytical queries, window functions), PySpark/Spark SQL, and data modeling fundamentals - Bachelor’s degree in MIS, Computer Science, Engineering, or equivalent experience - Proficiency with SQL and Python (PySpark), including performance tuning on large datasets - Experience with Azure Databricks, Delta Lake, Delta Live Tables (DLT), Azure Data Factory (or Fabric Data Pipelines), ADLS Gen2, and Azure DevOps/Git for CI/CD - Working knowledge of Unity Catalog and/or Microsoft Purview for governance, lineage, and security - Familiarity with data ingestion patterns (files, APIs, JDBC), schema evolution, CDC, and deletion detection patterns - Understanding of dimensional modeling to produce analytics‑ready datasets for Power BI - Exposure to orchestration/monitoring, cost optimization, alerting, and runbook‑driven operations - Data pipeline design (batch & streaming), DLT expectations for data quality, and robust error handling - Source control, branching strategies, and CI/CD for data assets (notebooks, jobs, workflows) - Practical understanding of privacy, security, and RBAC in cloud data platforms - Excellent communication, documentation, and cross‑functional collaboration skills - Analytical mindset; bias toward automation and measurable reliability - Applicants must be legally authorized to work in the United States and should not require now, or in the future, sponsorship for employment visa sponsorship. Requirements - Design, implement, and support end‑to‑end ELT pipelines (ingest → transform → publish) in Databricks/ADF - Implement data quality checks (DLT expectations, unit tests) with alerting and remediation runbooks - Build curated, analytics‑ready Delta tables using dimensional modeling for consumption by BI Developers - Implement CDC and deletion‑flag patterns; manage schema drift and partitioning/Z‑Ordering strategies - Operationalize jobs with monitoring, logging, alerting; participate in an on‑call rotation as needed - Partner with the Data Architect to align designs with standards for governance, security, and cost efficiency - Document pipelines, data contracts, and SLAs; continuously improve performance and reliability Working Conditions - This position is remote - Occasional travel may be required for training or meetings. - Must be able to work flexible hours to accommodate different time zones (Central/Eastern/Mountain/Pacific), if necessary. - Be flexible for after-hours tasks, as needed. Benefits - Medical, dental, vision and life insurance coverage - Competitive pay and a matching 401 (k) plan - Vacation, Company Holidays, Paid Time Off (PTO- personal and sick days) - Flexible spending accounts/Health savings account - Wellness Incentive Programs - Employee Referral Program - Tuition Reimbursement

Role Description We are looking for a Senior Data Engineer to design, build, and operate a scalable, cloud-native data platform that supports both analytics and AI-driven use cases. This role goes beyond traditional data warehousing. You will work closely with AI engineers to build the data foundation that powers LLM applications, agent-based systems, and RAG solutions. You will be responsible for: - Building reliable data pipelines - Developing curated data models and products - Ensuring high-quality, trusted data is readily available for analytics and AI workloads Qualifications - 5+ years of hands-on experience in Data Engineering with proven delivery in production environments - Strong expertise in building scalable data pipelines using Python and SQL - Hands-on experience with modern data engineering tools such as dbt, Airflow, Prefect, or similar - Strong experience with dimensional data modeling and semantic data models - Experience working with cloud platforms (AWS preferred), including services such as S3, Redshift, Athena, Glue, and Lambda - Hands-on experience designing, building, and operating modern data infrastructure, including storage, compute, orchestration, and monitoring - Familiarity with modern AI architectures and the data requirements for LLMs, AI agents, and RAG applications Requirements - Strong ownership mindset with the ability to thrive in a fast-paced startup environment - Ability to translate evolving business, analytics, and AI requirements into scalable data solutions - Effective communicator who collaborates well across Data, AI, Product, and Engineering teams - A senior engineer who balances architectural thinking with hands-on execution Benefits - Growth opportunity: Join an AI-forward company driving innovation through artificial intelligence - Direct impact: Your work will be at the center of how we grow revenue, support customers, and differentiate in the market - Autonomy and Accountability: We value autonomy and accountability — there’s no bureaucracy or lengthy approval process - Work for a Market Leader: Scale a project that counts market-leading companies like Microsoft, Mastercard, and more as happy customers - Leadership visibility: Reporting into the Data Lead which means your projects will be strategic and business-critical - Compensation and perks are great: Competitive compensation and 100% remote work - Culture: Work with some of the best colleagues coming from top tech companies, leading with respect, kindness, and the right to fail