Harnham
Senior Data Modeler / Analytics Engineer – Phoenix, AZ
We’re hiring a
Senior Data Modeler / Analytics Engineer
to help lead a
greenfield data transformation
within a large, modern data organization. This is a high-impact, highly visible role focused on building
enterprise-grade data models
that power analytics, BI, and decision-making across the business.
You’ll sit at the intersection of
data modeling, data engineering, and business partnership , helping define standards from scratch while working hands‑on with cloud‑native platforms.
Base Pay Range $140,000.00/yr - $150,000.00/yr
What You’ll Do
Lead
enterprise‑grade data modeling
across analytics and data platform teams, with a primary focus on analytical, semantic, and kinetic models
Design and maintain
conceptual, logical, and physical data models
that accurately represent complex business domains
Build
time‑variant and change‑aware models
(e.g., SCD patterns) that support historical analysis and evolving business questions
Define and implement
modeling standards, naming conventions, and governance
in a greenfield environment
Partner with data engineers to architect and implement
scalable, cloud‑native pipelines
aligned to medallion architecture principles
Support and optimize
analytics and BI consumption layers , ensuring performance, consistency, and usability
Serve as a technical advisor across data engineering and analytics teams on modeling best practices
Mentor and train junior data engineers on modern data modeling techniques and patterns
Translate technical data structures and tradeoffs into clear guidance for non‑technical stakeholders
Required Technical Skills
5–7+ years of hands‑on experience in
data modeling, analytics engineering, or data engineering
Expert‑level proficiency in
SQL , including complex transformations and time‑based modeling
Deep experience with
conceptual, logical, and physical data modeling
methodologies
Proven experience modeling
slowly changing dimensions
and longitudinal datasets
Strong understanding of
analytics engineering best practices
and semantic layer design
Hands‑on experience with
Snowflake
or comparable cloud data warehouses
Experience working within
AWS‑based
data platforms
Practical knowledge of
medallion architecture
and layered data design
Experience using
dbt
for data transformation, testing, and documentation
Familiarity with data modeling and diagramming tools such as
SQL DBM
and
Lucid
Preferred Qualifications
Python for data engineering or analytical workflows
Experience with
streaming platforms
such as Kafka or Kinesis
Background in
reverse engineering legacy data models , including Informatica‑based systems
Exposure to
agent‑based or co‑pilot tooling
to accelerate development
Prior experience integrating data models with enterprise BI tools
Why This Role
Opportunity to
define data modeling standards from the ground up
in a greenfield environment
High‑impact role with influence across analytics, data engineering, and platform teams
Direct collaboration with business and domain experts to shape analytics strategy
Strong long‑term investment in modern data platforms and cloud technologies
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Environmental Services, Technology, Information and Media, and Engineering Services
Benefits
Medical insurance
Vision insurance
#J-18808-Ljbffr
Senior Data Modeler / Analytics Engineer
to help lead a
greenfield data transformation
within a large, modern data organization. This is a high-impact, highly visible role focused on building
enterprise-grade data models
that power analytics, BI, and decision-making across the business.
You’ll sit at the intersection of
data modeling, data engineering, and business partnership , helping define standards from scratch while working hands‑on with cloud‑native platforms.
Base Pay Range $140,000.00/yr - $150,000.00/yr
What You’ll Do
Lead
enterprise‑grade data modeling
across analytics and data platform teams, with a primary focus on analytical, semantic, and kinetic models
Design and maintain
conceptual, logical, and physical data models
that accurately represent complex business domains
Build
time‑variant and change‑aware models
(e.g., SCD patterns) that support historical analysis and evolving business questions
Define and implement
modeling standards, naming conventions, and governance
in a greenfield environment
Partner with data engineers to architect and implement
scalable, cloud‑native pipelines
aligned to medallion architecture principles
Support and optimize
analytics and BI consumption layers , ensuring performance, consistency, and usability
Serve as a technical advisor across data engineering and analytics teams on modeling best practices
Mentor and train junior data engineers on modern data modeling techniques and patterns
Translate technical data structures and tradeoffs into clear guidance for non‑technical stakeholders
Required Technical Skills
5–7+ years of hands‑on experience in
data modeling, analytics engineering, or data engineering
Expert‑level proficiency in
SQL , including complex transformations and time‑based modeling
Deep experience with
conceptual, logical, and physical data modeling
methodologies
Proven experience modeling
slowly changing dimensions
and longitudinal datasets
Strong understanding of
analytics engineering best practices
and semantic layer design
Hands‑on experience with
Snowflake
or comparable cloud data warehouses
Experience working within
AWS‑based
data platforms
Practical knowledge of
medallion architecture
and layered data design
Experience using
dbt
for data transformation, testing, and documentation
Familiarity with data modeling and diagramming tools such as
SQL DBM
and
Lucid
Preferred Qualifications
Python for data engineering or analytical workflows
Experience with
streaming platforms
such as Kafka or Kinesis
Background in
reverse engineering legacy data models , including Informatica‑based systems
Exposure to
agent‑based or co‑pilot tooling
to accelerate development
Prior experience integrating data models with enterprise BI tools
Why This Role
Opportunity to
define data modeling standards from the ground up
in a greenfield environment
High‑impact role with influence across analytics, data engineering, and platform teams
Direct collaboration with business and domain experts to shape analytics strategy
Strong long‑term investment in modern data platforms and cloud technologies
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Environmental Services, Technology, Information and Media, and Engineering Services
Benefits
Medical insurance
Vision insurance
#J-18808-Ljbffr