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Analytics Engineer
Career Insights for Data Engineer
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Based on Pennsylvania data
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What they do
A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.
$113,315 / year median in Pennsylvania
+12% projected growth
Job Description
This is a 6-month contract position for an Analytics Engineer located in Philadelphia, Pennsylvania. You will develop and maintain scalable data models, ELT pipelines, and trusted datasets that support enterprise analytics, reporting, and self-service BI. You will partner 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. Qualifications Required 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 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. Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related field.