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Sr Data Engineer Jobs in Arizona (NOW HIRING)

Senior Data & AI Engineer

Phoenix, AZ · Remote

$100K - $136K/yr

Position Profile The Senior Data & AI Engineer will need to have deep handson experience in Snowflake, Microsoft Fabric (incl. OneLake), and healthcare data ecosystems. The ideal candidate ...

Senior Data & AI Engineer

Phoenix, AZ · On-site

$100K - $136K/yr

Position Profile The Senior Data & AI Engineer will need to have deep hands‑on experience in Snowflake, Microsoft Fabric (incl. OneLake), and healthcare data ecosystems. The ideal candidate ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced ...

... Senior Data Scientist AI capabilities. The ideal candidate combines technical depth, business ... Partner with business, product, data, engineering, architecture, cybersecurity, legal, privacy ...

Senior Data Architect

Tucson, AZ · On-site

$64.75 - $86.75/hr

Senior Data Architect We are seeking a Senior Data Architect to join a project team that will be ... Provide technical leadership and mentorship to database administrators, database developers, and ...

Senior Data Architect

Phoenix, AZ

$66.75 - $89.25/hr

The Senior Data Architect is expected to operate from strategy through implementation, partnering with engineering teams to design scalable solutions while actively participating in architecture ...

Senior Data Architect

Phoenix, AZ

$66.75 - $89.25/hr

The Senior Data Architect is expected to operate from strategy through implementation, partnering with engineering teams to design scalable solutions while actively participating in architecture ...

Senior Data Architect

Tucson, AZ · On-site

$62.50 - $83.75/hr

Senior Data Architect We are seeking a Senior Data Architect to join a project team that will be ... Provide technical leadership and mentorship to database administrators, database developers, and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Senior GCP Data Engineer

Phoenix, AZ · On-site

$105K - $143K/yr

Senior GCP Data Engineer Job Location: Phoenix, AZ Job Type: Contract Data Engineering & Pipelines * Design and develop batch and streaming pipelines using Dataflow (Apache Beam) * Build real-time ...

Sr.Big Data Engineer

Phoenix, AZ

$55.25 - $73.25/hr

Sr. Big Data Engineer Location: Phoenix, AZ Job type: FTE Big Data exp.: 3+ years. Responsibilities (but not limited to): Implementation of various solutions arising out of the large data processing ...

Showing results 41-60

Sr Data Engineer information

See Arizona salary details

$75.5K

$117.7K

$163.1K

How much do sr data engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for sr data engineer in Arizona is $117,724.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,800.00 and $134,200.00 per year, depending on experience, location, and employer.

What is the difference between Sr Data Engineer vs Data Engineer?

AspectSr Data EngineerData Engineer
Required CredentialsBachelor's degree in CS or related field; 3+ years experience; SQL, Python, SparkBachelor's degree in CS or related field; 1-3 years experience; SQL, Python, Spark
Work EnvironmentCollaborates with data scientists, analysts; designs scalable data pipelinesBuilds and maintains data pipelines; supports data analysis
Employer & Industry UsageTech companies, finance, healthcare; used for complex data projectsStartups, enterprises; used for data collection and processing

The main difference between a Sr Data Engineer and a Data Engineer lies in experience level, responsibilities, and complexity of projects. Sr Data Engineers typically have more experience, handle more complex data architecture, and mentor junior staff, whereas Data Engineers focus on building and maintaining data pipelines. Both roles are essential in data-driven organizations, but the senior role involves greater technical leadership and strategic planning.

What are the key skills and qualifications needed to thrive as a Sr data engineer, and why are they important?

To thrive as a Sr Data Engineer, you need expertise in data architecture, ETL processes, programming (such as Python or Scala), and a strong background in computer science or a related field. Familiarity with big data technologies like Hadoop, Spark, cloud platforms (AWS, Azure, GCP), and database management systems, along with relevant certifications, is typically required. Advanced problem-solving abilities, attention to detail, and strong collaboration skills help set top performers apart in this role. These skills and qualities ensure the efficient design, implementation, and maintenance of robust data pipelines that enable data-driven decision-making across the organization.

How do Sr data engineers typically collaborate with data scientists and analysts within a project team?

Sr Data Engineers play a crucial role in bridging the gap between raw data and actionable insights. They work closely with data scientists and analysts to understand data requirements, design robust data pipelines, and ensure the reliability and scalability of data infrastructure. Regular collaboration involves translating analytical needs into technical specifications, optimizing data flow, and troubleshooting data issues. This teamwork ensures that data-driven projects progress smoothly and that the analytical team has timely access to clean, well-structured data.

What is a Sr data engineer?

Sr Data Engineers, or Senior Data Engineers, are experienced professionals responsible for designing, building, and maintaining scalable data pipelines and architectures. They work with large datasets, ensuring data quality, reliability, and accessibility for analytics and business intelligence purposes. Sr Data Engineers collaborate with data scientists, analysts, and other stakeholders to implement data solutions that support decision-making and business growth. Their expertise often includes proficiency in programming languages like Python or Java, experience with big data tools such as Hadoop or Spark, and a deep understanding of database systems.

What cities in Arizona are hiring for Sr Data Engineer jobs?

Cities in Arizona with the most Sr Data Engineer job openings:

Infographic showing various Sr Data Engineer job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $117,724 per year, or $56.6 per hour.

Senior Data & AI Engineer

Hospice of the Valley

Phoenix, AZ • Remote

$100K - $136K/yr

Full-time

PTO

Re-posted 20 days ago


Hospice Of The Valley (Arizona) rating

7.8

Company rating: 7.8 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

12th of 44 rated hospices


Job description

Join Arizona’s largest, most prominent not-for-profit hospice, serving the valley since 1977.

Hospice of the Valley is a national leader in hospice care and has been serving the Phoenix metropolitan area since 1977.  A mission-driven, not-for-profit organization, Hospice of the Valley employs compassionate, skilled professionals who are committed to excellence, enjoy teamwork, and contribute daily to our mission and culture of caring. Team members experience a friendly, supportive atmosphere, leadership support, autonomy, flexibility, and the privilege of doing meaningful, rewarding work.

Benefits:

  • Supportive work environment with a culture of caring for patients and one another.
  • Competitive wages and excellent benefit program.
  • Generous Paid Time Off.
  • Flexible schedules for work/life balance.

Position Profile

The Senior Data & AI Engineer will need to have deep handson experience in Snowflake, Microsoft Fabric (incl. OneLake), and healthcare data ecosystems. The ideal candidate understands data modeling, data integration, and data transformation across structured and unstructured sources, and can build machine learning pipelines that operate on claims and clinical data. You’ll design secure, scalable data platforms; map and normalize data across payers, providers, CMS datasets, EHR systems, and HIEs; and operationalize AI tools to drive measurable outcomes in cost, quality, and member/patient experience.

Responsibilities

Data Platform Engineering

  • Architect, implement, and optimize data solutions in Snowflake and Microsoft Fabric (incl. OneLake, Lakehouses, Warehouses, and Data Engineering pipelines).
  • Build robust ingestion frameworks for batch and streaming data (e.g., ADLS, EventHub, APIs, SFTP) with lineage and governance.
  • Manage data security, privacy, and compliance (HIPAA/PHI; rolebased access, masking, tokenization, deidentification).

Data Modeling & Integration

  • Design conceptual/logical/physical models (normalized, dimensional/star, data vault where appropriate).
  • Implement data mapping and transformations for structured (claims, eligibility, provider, enrollment) and unstructured (clinical notes, PDFs) data.
  • Harmonize healthcare data using FHIR/HL7/CCDA, X12/EDI 837/835, NCPDP, and CMS standards; reconcile and link records across EHR and HIE sources.

Analytics & Machine Learning

  • Build ML pipelines for risk stratification, cost/utilization forecasting, fraud/waste/abuse detection, quality measure computation (e.g., HEDIS), and care gap identification.
  • Operationalize models with MLOps (experiment tracking, reproducibility, CI/CD, monitoring, drift detection).
  • Leverage LLMs/AI tools for data quality, entity resolution, summarization, and clinical insights—ensuring safety, bias checks, and auditability.

Governance & Observability

  • Implement data cataloging, lineage, and metadata (e.g., Microsoft Purview or equivalent).
  • Establish quality SLAs, validation rules, profiling, and automated anomaly detection.
  • Instrument pipelines for cost, performance, and reliability (e.g., Snowflake resource monitors, Fabric capacities).

Collaboration & Delivery

  • Work with product owners, clinicians, actuaries, and analytics teams to translate requirements into scalable solutions.
  • Produce clear documentation, data dictionaries, and mapping specs; mentor engineers and analysts.
  • Contribute to architectural roadmaps, reference patterns, and best practices across the enterprise.

Maintains and enhances professional skills.

Adheres to high standards of personal and professional conduct.

Minimum Qualifications

  • 8+ years in data engineering/analytics; 5+ years handson with Snowflake (compute, storage, virtual warehouses, tasks, streams, Snowpipe, Time Travel, RBAC, row/column masking, data sharing, Dynamic Tables).
  • 2+ years with Microsoft Fabric (including OneLake, Lakehouses, Warehouses, Dataflows Gen2, Notebooks, Pipelines; capacity management).
  • Strong data modeling expertise (dimensional/star, 3NF, data vault; surrogate keys, SCD types, conformed dimensions).
  • Data integration & transformation proficiency: SQL (advanced), dbt or Fabric Dataflows/Power Query M, ADF/Synapse/Fabric Pipelines, Python for ETL/ELT.
  • Mapping from CMS data (e.g., Medicare datasets, claims/encounters), X12/EDI, FHIR/HL7, provider and eligibility.
  • Experience with structured (tables, CSV, Parquet) and unstructured (clinical notes, PDFs, blobs) data; NLP pipelines (optional but valued).
  • Machine learning: feature engineering, model training/evaluation, and deployment (e.g., scikitlearn, PyTorch/TensorFlow, Fabric ML/Notebook, Azure ML); production monitoring.
  • Security & compliance: HIPAA, PHI handling, auditing, data residency, BAAs; practical access control in Snowflake/Fabric.
  • Strong communication; ability to author mapping specs, lineage docs, and present tradeoffs to technical and nontechnical stakeholders.

Preferred Qualifications

  • Interoperability: FHIR R4, HL7 v2, X12/EDI (837/835), NCPDP; experience with HIEs and EHR integrations (Epic, Cerner, etc.).
  • CMS & payer/provider data: Medicare feeforservice, MA, Medicaid, CCW, APCD, and quality programs; risk adjustment (HCC), HEDIS measures.
  • MLOps & DevOps: MLflow, DVC, GitHub Actions/Azure DevOps, containerization (Docker), orchestration (Airflow, Fabric Pipelines, or ADF).
  • Governance: Microsoft Purview (catalog, lineage, classifications), data quality tools.
  • Visualization: Power BI and Fabric Direct Lake; semantic modeling and rowlevel security.
  • Cloud: Azure (ADLS, Event Hub, Functions, Key Vault, Databricks), optional AWS/GCP exposure.
  • Certifications: Snowflake SnowPro Core/Advanced, Microsoft Certified (Azure Data Engineer Associate, Fabric Analytics Engineer).

Hospice of the Valley is an equal employment opportunity employer. EOE/M/F/D/V


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