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Data Analytics Engineer Jobs in Philadelphia, PA

Armaninollp

Data & AI Platform Engineer

Philadelphia, PA

$115K - $138K/yr

This is an early-career engineering role focused on building, operating, and improving cloud data ... Data/Analytics Tooling Support * Assist teams with onboarding and "how-to" enablement across a core ...

1 point system

Sr. Data Engineer

Wayne, PA · On-site

$96K - $130K/yr

Requirement - Sr. Data Engineer Location- * 1041 West Valley Road Wayne, Pennsylvania 19087 * 7900 ... Provides data analysis guidance as required. * Designs and conducts training sessions on tools and ...

NAVA Software Solutions

Data Analyst

Malvern, PA · On-site

Data Analyst Engineer Location: Malvern, PA - Hybrid Duration: 6 -12 months Two Round Interview Process Round 1: Technical Interview Round 2: Case Study (Candidates will be given a takeaway case ...

Workiva

Spring 2027 Intern - Data Analytics

Trenton, NJ · On-site +1

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... September 27, 2026 Engineering postings close: October 2, 2026 Interviews: Early to mid October ...

Workiva

Spring 2027 Intern - Data Analytics

Trenton, NJ · On-site

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... September 27, 2026 Engineering postings close: October 2, 2026 Interviews: Early to mid October ...

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Showing results 41-60

All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Philadelphia, PA

Data Analytics Engineer information

See Philadelphia, PA salary details

$42.5K

$124K

$169.6K

How much do data analytics engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data analytics engineer in Philadelphia, PA is $123,973.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,400.00 and $131,400.00 per year, depending on experience, location, and employer.

How do data analytics engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to develop insights and reports.

What are the most commonly searched types of Data Analytics Engineer jobs in Philadelphia, PA?

The most popular types of Data Analytics Engineer jobs in Philadelphia, PA are:

What are popular job titles related to Data Analytics Engineer jobs in Philadelphia, PA?

For Data Analytics Engineer jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Data Analytics Engineer jobs in Philadelphia, PA look for?

The top searched job categories for Data Analytics Engineer jobs in Philadelphia, PA are:

Data Analytics Engineer jobs near you
Infographic showing various Data Analytics Engineer job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $123,973 per year, or $59.6 per hour.

Director, Data & Intelligence

Clarivate Analytics US LLC

Philadelphia, PA • On-site

Other

Posted 4 days ago

Job description

We are looking for a Director,Dataand Intelligence to lead our enterprise data, business intelligence and reporting capabilities. This is an opportunity to shape enterprise reporting across Finance, Sales, Customer Service,Operationsand other corporate functions, as well as customer and product usage reporting.

This hands-on build-and-run leadership role willestablisha stable,governedand scalable operating model across a technology landscape that includes Snowflake, AWS Redshift, Databricks, Microsoft Fabric, Power BI,Pendoand Snowplow. We would love to speak with you if you bring strong practical experience in enterprise reporting, modern cloud dataarchitecturesand data-platform transformation, with the leadership depth to guide specialists and connect data investments to business outcomes.

About You - experience, education, skills, and accomplishments

  • Bachelor's or Master'sdegree, or equivalent practical experience, in data, analytics, technology, engineering, computer science ora relatedfield.
  • At least 10 years of relevant experience across data, analytics,reportingor data-platform delivery.
  • At least 5 years of leadership experience managing data, BI,engineeringor analytics teams.
  • Experience owning enterprise reporting and business intelligence in a complex organization.
  • Strong practical understanding of Snowflake, PowerBIand modern cloud data architectures, with working knowledge of AWS Redshift, Databricks and Microsoft Fabric.

It would be great if you also had . . .

  • Experience with customer or product usage analytics, including Pendo,Snowplowor comparable technologies.
  • Experience leading data migration, reporting transformation or enterprisedata-platforminitiatives.
  • Strong understanding of data engineering, dimensional modeling, semantic models, ETL/ELTand data-quality practices.
  • Experience integrating data from CRM, ERP, Finance and operational systems, directing specialistpartnersand translating business questions into sustainable reporting solutions.
  • Corporate carve-out, separation,mergeror TSA exit experience.
  • Experience with Snowflake administration, architecture and cost management, or Microsoft Fabric,OneLake, Power BI governance andsemantic-modelmanagement.
  • Experience with AWS data services, including Redshift, S3 and Glue, or Databricks, Delta Lake and Unity Catalog.
  • Experience with Pendo and Snowplow data ingestion and usage-reporting models, or enterprise reporting across Salesforce,NetSuiteand Finance applications.
  • Experience with data catalogs, lineage, master data, data governance orestablishinga controlled self-service analytics model.

What will you be doing in this role?

Data and intelligence leadership:Own the strategy, roadmap and operating model for enterprise data, analytics and reporting,establishingclear ownership and translating business priorities into practical plans.

Enterprise and usage reporting:Oversee executive dashboards, management reporting, operational reports, self-service analytics and customer and product usage reporting, with consistent definitions and trusted sources.

Platforms and architecture:Set direction across Snowflake, AWS Redshift, Databricks, Microsoft Fabric and Power BI, defining the role of each platform and ensuring scalable,secureand supportable architecture.

Data engineering,governanceand quality:Lead pipelines, modeling,transformationand integration whileestablishingpractical governance for ownership, lineage, classification, access,retentionand data quality.

Delivery and operational stability:Lead discovery, architecture, migration, engineering, validation, cutover,stabilizationand handover while protecting reporting continuity and data integrity.

Team and partner leadership:Lead a multidisciplinary team of data engineers, BI developers, data analysts, platformspecialistsand product owners, and manage specialist partners, budgets, platform costs,licensingand resource plans.

About the Team

The Data and Intelligence team supports enterprise data, analytics and reporting across Finance, Sales, Customer Service,Operationsand other corporate functions, along with customer and product usage reporting. The multidisciplinary team includes data engineers, BI developers, data analysts, platformspecialistsand product owners. This role will partner with business leaders and Enterprise Architecture, Cloud, Security, Privacy, Compliance, Application, Product Technology and Product Operations teams, as well as systems integrators and specialist partners.

Hours of Work

  • Full-time permanent position primarily working core business hours in your time zone, with flexibility to adjust to various global time zones as needed.
  • Hybrid position working 2-3 days per week on-site.
  • Must live within a commutable distance of the Philadelphia, PA office.

At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations.

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