> Markdown version of [/jobs/ext/3224564-data-engineer-ii](https://www.wearedevelopers.com/jobs/ext/3224564-data-engineer-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer II - **Company:** Personify Inc - **Location:** Tempe, AZ, United States - **Salary:** $86,700.0 - $170,900.0 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Business Analytics Applications, Data Analysis, JIRA, Build Automation, Cloud Computing, Cloud Engineering, Information Systems, Databases, Continuous Integration, Directed Acyclic Graph (Directed Graphs), Information Engineering, Data Files, Extract Transform Load (ETL), Data Mining, Data Warehousing, Relational Databases, Database Queries, Dimensional Modeling, Django Web Framework, UN Electronic Data Interchange for Administration Commerce and Transport, JSON, Python (Programming Language), PostgreSQL, MicroStrategy, Oracle (Applications), Parsing, Power BI, SQL Databases, Data Streaming, Tableau (Software), Scripting, Snowflake, Git, Amazon Relational Database Service, Information Technology, Health Level Seven International, Bitbucket, Cloudwatch, Restful APIs, Terraform, Data Pipelines, Docker - **Published:** September 4, 2026 - **Apply:** https://www.careerjet.com/job/us663183c1453f2b829832c9a4312542b9/eaa ## About the Role * Bachelor's degree in computer science, information systems, or a related field, or equivalent experience * 3+ years in data engineering or analytics engineering, ideally within TPA, healthcare, insurance, or claims processing * 1+ years in system/data analysis or process improvement * 1+ years in the healthcare industry preferred * AWS Certification preferred: AWS Certified Cloud Practitioner, Developer - Associate, or Data Engineer - Associate Technical Skills: * Proficient in Python and SQL, including complex queries (pivots, window functions, date calculations) * Hands-on experience with orchestration tools (Airflow), containers (Docker), and CI/CD pipelines * Exposure to healthcare EDI transactions (834, 835, 837, 2222, 2223, 999) preferred * Exposure to data files like OMS or HL7, or ability to parse delimited files into a database using Python scripting * Familiarity with REST APIs, JSON, and non-relational data models, including converting that data into relational models * Experience with JIRA, BitBucket Git, and BitBucket Pipelines * Proficient in Excel; familiar with analytical tools like Tableau, Power BI, or MicroStrategy * Solid understanding of data modeling concepts (star/snowflake schemas, dimensional modeling) and relational vs. non-relational models * Working knowledge of AWS services (S3, Glue, EC2, MWAA, Lambda, ECS) a plus; Infrastructure as Code (Terraform) a plus * Experience with relational databases (PostgreSQL, Oracle, AWS RDS); exposure to modern data warehouses (Snowflake, Redshift) a plus ## Description Every claim, eligibility check, and provider record that flows through our systems depends on pipelines that work - every time, without exception. As a Data Engineer II, you're the person who builds and maintains that backbone, turning raw healthcare and TPA data into clean, reliable information that analysts, business teams, and ultimately our clients and members can count on. When a pipeline breaks or data goes bad, real people feel it - a claim gets delayed, a report goes out wrong, a decision gets made on bad numbers. Your work closing that gap between messy source data and trustworthy systems is what lets the rest of the organization move fast with confidence. Get the pipelines right, and you're not just moving data - you're moving outcomes for the members and clients who rely on us. What You'll Actually Do * Build ETL/ELT pipelines: Design and maintain pipelines that ingest and transform healthcare and TPA data - including claims, provider, and eligibility sources - turning raw feeds into usable, trustworthy data sets. * Orchestrate and monitor workflows: Develop, schedule, and monitor pipelines using Airflow, CloudWatch, ECS, and DAGs, following established CI/CD, observability, and governance practices to keep data flowing reliably. * Develop data applications: Build workflows and applications using Python, SQL, and Django, working across PostgreSQL, Oracle, and cloud-native databases to power downstream reporting and analysis. * Support core healthcare data processes: Manage EDI file transfers, claims adjudication support, audits, and reporting workflows that keep compliance and operations on track. * Own data extraction and documentation: Extract, cleanse, and load new data sets, investigating and documenting source systems so the team always knows what it's working with. * Translate requirements into solutions: Partner with Data Analysts, Data Scientists, Product, Reporting, and Account Management to turn business needs into working data pipelines. * Safeguard data quality and compliance: Implement quality assurance rules and automated validation that keep data accurate, complete, and secure under HIPAA and CMS regulations. * Troubleshoot and resolve pipeline issues: Monitor pipeline health, triage incoming bugs and incidents, and resolve data flow issues - escalating complex architectural problems to senior engineers when needed. * Contribute to data modeling decisions: Apply data modeling patterns and standards set by senior engineers, contributing your perspective to pipeline design discussions. * Guide junior engineers: Help onboard and mentor Data Engineer I team members, sharing what you learn so the whole team levels up. * Automate routine work: Build automation for repetitive operational workflows and reporting, cutting out manual busywork wherever possible. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [GitOps for the people](https://www.wearedevelopers.com/videos/461-gitops-for-the-people) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Best Paying Jobs in Technology](https://www.wearedevelopers.com/magazine/256-best-paying-jobs-in-technology)