Requisition Number: 103994 Principal Software Engineer - Data Location: You will have the flexibility to work fully remote from anywhere across the US. Insight at a Glance - 14,000+ engaged teammates globally - Received 35+ industry and partner awards in the past year Now is the time to bring your expertise to Insight. We are not just a tech company; we are a people-first company. We believe that by unlocking the power of people and technology, we can accelerate transformation and achieve extraordinary results. As a Fortune 500 Solutions Integrator with deep expertise in cloud, data, AI, cybersecurity, and intelligent edge, we guide organizations through complex digital decisions. About the role We are seeking a Principal Data Engineer to serve as a senior technical leader within our Data & AI Business Unit. This role represents the highest level of individual contributor for data engineering and is a natural progression toward Solutions or Data Architecture roles. As a Principal Data Engineer, you will lead the design and implementation of complex data pipelines and platforms, influence architectural decisions, establish engineering standards, and mentor other engineers—while remaining deeply hands on. Responsibilities - Design, build, and optimize scalable, reliable data pipelines and platforms - Lead technical implementation across ingestion, transformation, and data serving layers - Translate architectural direction into production ready engineering solutions - Influence and contribute to data platform and solution architecture decisions - Establish and enforce engineering standards, patterns, and best practices - Serve as a technical mentor and escalation point for senior and mid level engineers - Partner closely with architects, analytics, BI, and AI teams to deliver end to end solutions - Own performance tuning, reliability, and operational excellence of data systems - Review designs and code to ensure quality, scalability, and maintainability - Stay current on modern data engineering tools, frameworks, and architectural trends Travel & Work Environment - Hybrid or remote work environment (US based) - Occasional travel to support planning, delivery, or team collaboration - Fast paced, collaborative engineering culture focused on quality and scale What we’re looking for - 8+ years of experience in data engineering or data platform development - Experience operating as a Senior or Principal level engineer on complex data initiatives - Strong expertise in data pipeline development (batch and/or streaming) - Deep hands-on experience with cloud data platforms (Azure, AWS, or GCP) - Advanced SQL skills and solid experience with data modeling practices - Strong programming experience in Python, SQL, and/or Spark - Proven ability to influence technical direction without direct authority - Experience working in collaborative, cross functional environments - Ability to clearly communicate tradeoffs, risks, and implementation details Certifications - Cloud or data platform certifications preferred (Azure, AWS, GCP, Databricks, Snowflake, Fabric, etc.) What you can expect We’re legendary for taking care of you, your family and to help you engage with your local community. We want you to enjoy a full, meaningful life and own your career at Insight. Some of our benefits include: - Freedom to work from another location, even an international destination, for up to 30 consecutive calendar days per year. - Comprehensive benefits package including medical, dental, vision, and company 401k match. But what really sets us apart are our core values of Hunger, Heart, and Harmony, which guide everything we do, from building relationships with teammates, partners, and clients to making a positive impact in our communities. Join us today, your ambITious journey starts here. When you apply, please tell us the pronouns you use and any reasonable adjustments you may need during the interview process. At Insight, we celebrate diversity of skills and experience so even if you don’t feel like your skills are a perfect match - we still want to hear from you! Compensation Range - Base Salary: $130,000 – $150,000, based on experience The position described above provides a summary of some the job duties required and what it would be like to work at Insight. For a comprehensive list of physical demands and work environment for this position, click here. Insight is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law. Posting Notes: Remote, AZ || Arizona (US-AZ) || United States (US) || IT Infrastructure & Support || None || US - Chandler,AZ ||

• Assist in building and maintaining ETL/ELT pipelines for healthcare datasets including claims, eligibility, provider, risk adjustment, HEDIS, EHR, and clinical data • Support the development of data models and data transformations aligned with healthcare standards (e.g., HL7, FHIR, X12) • Contribute to data quality checks, validation rules, and documentation for healthcare data assets • Work with analysts and business users to understand data requirements and translate them into technical tasks • Assist in ingestion and integration of new data sources from EMR systems, CMS feeds, and vendor partners • Develop SQL queries, transformations, functions, and stored procedures to support reporting and analytics workflows • Support data platform tools such as Azure Data Factory, Databricks, Python/Spark jobs, and version control workflows • Participate in issue resolution related to data pipeline failures or data quality errors • Maintain data dictionaries, mapping files, and documentation as part of data governance processes • Collaborate with senior engineers to implement best practices in security, compliance (HIPAA), and architecture

• Design, implement, and continuously expand data pipelines by performing extraction, transformation, and loading (ETL) activities • Gather requirements and business process knowledge to transform data in ways that meet end-user needs • Create new SDLC processes as needed and maintain and improve existing processes • Ensure data architecture is scalable and maintainable • Collaborate with business stakeholders and colleagues to design and deliver accurate, high-quality data • Investigate data to identify potential issues within ETL pipelines, notify end users, and propose effective solutions • Prepare and maintain documentation for future reference • Additional duties as assigned

Role DescriptionDropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that span multiple lines of business while driving standardization in how we build, deploy, and govern analytics pipelines across Dropbox. This is not a maintenance role. We are modernizing our analytics platform, upgrading orchestration infrastructure, building shared and reusable data models with conformed dimensions, establishing a certified metrics framework, and laying the foundation for AI-native data development. You will partner closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams to make this happen. You will play a crucial role in establishing analytics engineering standards, designing scalable data models, and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership, shape the technical direction of analytics infrastructure at Dropbox, and directly influence how data powers product and business decisions. Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here. Responsibilities - Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions - Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards - Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access - Architect and implement a shift-left data governance strategy, working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production - Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement - Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable - Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying. Requirements - BS degree in Computer Science or related technical field, or equivalent technical experience - 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership - 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL) - 8+ years of Python development experience, including building and maintaining production data pipelines - Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains - Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns - Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries Preferred Qualifications - Experience with Databricks (Unity Catalog, Delta Lake) and modern lakehouse architectures - Experience leading orchestration or platform modernization efforts at scale - Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar - Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, Databricks Metric Views, or equivalent) - Track record of establishing data engineering standards and best practices in a federated analytics organization CompensationUS Zone 1 This role is not available in Zone 1 US Zone 2 $198,900—$269,100 USD US Zone 3 $176,800—$239,200 USD