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Analytics Engineer Jobs in Pennsylvania (NOW HIRING)

Credit Genie

Director of Analytics

Plymouth Meeting, PA · On-site

$215K - $260K/yr

As Director of Analytics, you will lead the analytics strategy that informs product decisions ... You will partner with Product, Marketing, Risk, Engineering, and User Research to define success ...

APR Supply Co.

Senior Data Engineer- MS Fabric

Lebanon, PA · On-site

$104K - $141K/yr

Data lineage and impact analysis * Sensitivity labels and classification * Data discovery and ... Mentor analysts and engineers working within Fabric * Communicate clearly with both executives and ...

Socket.dev

$150 - $190/hr

As Director of Analytics, you will lead the analytics strategy that informs product decisions ... You will partner with Product, Marketing, Risk, Engineering, and User Research to define success ...

New

jobr.pro

Director of Analytics

Plymouth Meeting, PA · On-site

$130 - $160/hr

As Director of Analytics, you will lead the analytics strategy that informs product decisions ... You will partner with Product, Marketing, Risk, Engineering, and User Research to define success ...

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All JobsAnalytics Engineer JobsAnalytics Engineer Jobs in Pennsylvania

Analytics Engineer information

See Pennsylvania salary details

$56.2K

$98.2K

$160.2K

How much do analytics engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for analytics engineer in Pennsylvania is $98,196.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,330.00 and $110,220.00 per year, depending on experience, location, and employer.

What do analytics engineers do?

Analytics engineers design, build, and maintain data pipelines and infrastructure to enable data analysis and reporting. They work with tools like SQL, Python, and data warehouses to ensure data is accurate, accessible, and well-structured for analysts and data scientists. Their role often involves collaborating with teams to optimize data workflows and ensure data quality.

What are the key skills and qualifications needed to thrive as an analytics engineer, and why are they important?

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

How does an analytics engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

What is an analytics engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.
What are the most commonly searched types of Analytics Engineer jobs in Pennsylvania? The most popular types of Analytics Engineer jobs in Pennsylvania are:
What are popular job titles related to Analytics Engineer jobs in Pennsylvania? For Analytics Engineer jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Analytics Engineer jobs in Pennsylvania look for? The top searched job categories for Analytics Engineer jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Analytics Engineer jobs? Cities in Pennsylvania with the most Analytics Engineer job openings:
Analytics Engineer jobs near you
Infographic showing various Analytics Engineer job openings in Pennsylvania as of August 2026, with employment types broken down into 84% Full Time, 10% Part Time, 5% Contract, and 1% Nights. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $98,196 per year, or $47.2 per hour.

Sr Manager, Analytics & Insights

Thermo Fisher Scientific

Pittsburgh, PA

Full-time

Re-posted yesterday

Thermo Fisher Scientific rating

7.7

Company rating: 7.7 out of 10

Based on 423 frontline employees who took The Breakroom Quiz

198th of 538 rated manufacturers

Job description

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

At Thermo Fisher Scientific, our mission is to enable our customers to make the world healthier, cleaner, and safer. We are seeking a Senior Manager, Analytics & Insights to lead the strategy, development, and operation of our enterprise analytics capabilities. 
 

This role will drive the analytics roadmap, deliver scalable data and reporting solutions, and advance a data-driven culture across the organization. The Senior Manager will partner closely with business and technology leaders while leading a global team of analytics professionals, data scientists, architects, and engineers to improve commercial performance, customer experience, supply chain operations, and strategic decision-making. 
 

MAJOR JOB DUTIES AND RESPONSIBILITIES

  • Define and execute the enterprise analytics strategy, roadmap, and investment priorities. 
  • Play a pivotal role in the modernization of Thermofisher Digital Analytics; roadmap migration to AI supported insights 
  • Build scalable analytics and reporting capabilities that support customer, commercial, and operational objectives. 
  • Establish a trusted, enterprise-wide data foundation that enables consistent reporting and decision-making. 
  • Partner with business stakeholders to identify opportunities, solve complex problems, and deliver sustainable analytics solutions. 
  • Generate actionable insights through analytics, experimentation, KPI reporting, and performance measurement. 
  • Lead the design, implementation, and continuous improvement of cloud-based analytics platforms, data infrastructure, and data pipelines. 
  • Establish standards for data architecture, governance, security, and analytics engineering. 
  • Collaborate with product, architecture, and security teams to define requirements and prioritize initiatives. 
  • Build, lead, and develop a high-performing global analytics organization of approximately 3 to 5 associates. 
  • Foster a culture of innovation, continuous improvement, and data-driven decision-making. 
  • Lead cross-functional analytics and data transformation programs while balancing competing business priorities. 
  • Communicate analytics strategies, recommendations, and outcomes to executive leadership and key stakeholders. 
  • Manage relationships with external vendors, consultants, and technology partners. 

QUALIFICATIONS (Education/Training, Experience and Certifications) 

  • Bachelor's degree in Computer Science, Engineering, Information Systems, Business Analytics, or a related field; Master's degree preferred. 
  • 8+ years of experience in analytics, business intelligence, data engineering, data science, or related disciplines. 
  • 3+ years of leadership experience managing analytics, data engineering, or data science teams. 
  • Proven success building and leading high-performing analytics organizations and enterprise-scale platforms. 
  • Experience architecting, implementing, and supporting modern analytics infrastructure and cloud-based data solutions. 
  • Expertise with analytics and visualization tools such as Tableau, Power BI, Google Analytics, or Adobe Analytics. 
  • Experience with data warehouse technologies such as Snowflake, Teradata, Hadoop, or similar platforms. 
  • Strong SQL skills and experience with Python, ETL/ELT development, and modern data integration practices. 
  • Familiarity with AWS, Azure, or Google Cloud Platform; SAP and ERP integration experience preferred. 
  • Experience developing AI-enabled analytics solutions, including agentic and conversational interfaces that improve access to data, insights, and decision-making across the enterprise preferred. 
  • Knowledge of advanced analytics, machine learning, and predictive modeling preferred. 
  • Strong communication, stakeholder management, problem-solving, and organizational leadership skills. 
  • Ability to influence decision-making, manage competing priorities, and thrive in a fast-paced environment. 
  • Up to 25% travel may be required. 

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