Analytics Engineer

COREHIRE; Philadelphia (Philadelphia County); On-site; USD 120,000 - 150,000; Full time

Job summary

COREHIRE is seeking an Analytics Engineer II to design and maintain scalable data models, ELT pipelines, and trusted datasets for enterprise analytics. You will partner with analysts, data scientists, and engineers to deliver high-quality data products and ensure data quality, performance, and reliability.

This is an onsite, 6-month contract in Philadelphia, with potential to convert to FTE. Your responsibilities include dimensional modeling, building automated pipelines, and supporting BI

Qualifications

• 6 years in Data Analytics, Analytics Engineering, BI, or Data Engineering.
• Advanced SQL skills with complex transformations and performance tuning.
• Strong Data Warehousing and Dimensional Data Modeling experience.

Responsibilities

• Design and maintain dimensional data models and curated datasets.
• Develop automated, scalable ELT pipelines.
• Implement data quality monitoring, testing, and automation.
• Partner with business users, analysts, and data scientists to deliver analytics solutions.
• Support BI platforms, reporting, and dashboard migrations.
• Use software development best practices including Git, code reviews, and CI/CD.
• Collaborate with Data Engineering, DevOps, and Architecture teams.
• Participate in Agile/Scrum ceremonies and production support.

Skills

Advanced SQL

Data Warehousing

Dimensional Data Modeling

APIs

Python

Git

CI/CD

Analytical thinking

Education

Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or related field

Tools

Snowflake

dbt

Power BI

Git

CI/CD

APIs

Python

Job description

Analytics Engineer II

Location: Philadelphia, PA (Onsite)

Duration: 6 Months -- possible conversion to FTE

Type: W2

Overview

The Analytics Engineer develops and maintains scalable data models, ELT pipelines, and trusted datasets that support enterprise analytics, reporting, and self-service BI. This role partners with business stakeholders, analysts, data scientists, and engineers to deliver high-quality data products and ensure data quality, performance, and reliability.

Responsibilities

• Design and maintain dimensional data models and curated datasets.
• Develop automated, scalable ELT pipelines.
• Implement data quality monitoring, testing, and automation.
• Partner with business users, analysts, and data scientists to deliver analytics solutions.
• Support BI platforms, reporting, and dashboard migrations.
• Use software development best practices including Git, code reviews, and CI/CD.
• Collaborate with Data Engineering, DevOps, and Architecture teams.
• Participate in Agile/Scrum ceremonies and production support.

Required Experience

• 6 years in Data Analytics, Analytics Engineering, BI, or Data Engineering.
• Advanced SQL skills, including complex transformations and performance tuning.
• Strong Data Warehousing and Dimensional Data Modeling experience.
• Experience designing and maintaining Fact and Dimension tables.
• Hands-on experience with Snowflake.
• Experience developing analytics models using dbt.
• Experience with data quality testing and validation.
• Experience with Git, code reviews, and CI/CD.
• Experience with BI tools such as Power BI, Tableau, Qlik, or Business Objects.
• Experience with big data technologies such as Spark, Hadoop, Kafka, Hive, or Sqoop.
• Experience building and consuming APIs.
• Linux experience (RHEL/Debian).
• Scripting experience using Python, Bash, or similar languages.
• Strong analytical and problem-solving skills.
• Experience working in Agile environments.

Preferred Experience

• 8 years in data and analytics.
• Experience with Cloud platforms (AWS, Azure, or GCP).
• Experience with Apache Airflow or similar orchestration tools.
• Experience supporting BI migrations to Power BI.
• Experience with semantic models and analytics engineering best practices.

Education

Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related field preferred. Equivalent professional experience will be considered.

Must-Have Keywords

SQL, Snowflake, dbt, Dimensional Data Modeling, Fact Tables, Dimension Tables, Power BI