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Data Analytics Engineer Jobs in Philadelphia, PA

Enterprise Solutions, Web Development, Data Warehousing, Systems Integration, IT Security, Storage ... Analytics Engineer Location : Philadelphia, PA Duration : long Job Summary A highly experienced ...

Graduate degree in Computer Science, Data Analytics, Information Systems, or related field or equivalent work experience * 2+ years of experience in SQL programming (e.g. MSSQL, Oracle, or similar ...

Data Engineer

Philadelphia, PA · Remote

$117K - $140K/yr

The Opportunity We're looking for a Data / Analytics Engineer to own the data infrastructure that powers Arbor's intelligence layer. You'll be the connective tissue between our production systems and ...

Graduate degree in Computer Science, Data Analytics, Information Systems, or related field or equivalent work experience * 2+ years of experience in SQL programming (e.g. MSSQL, Oracle, or similar ...

Graduate degree in Computer Science, Data Analytics, Information Systems, or related field or equivalent work experience * 2+ years of experience in SQL programming (e.g. MSSQL, Oracle, or similar ...

Data Engineer

Malvern, PA · On-site

$112K - $134K/yr

Data Engineer Location : Malvern, PA Hybrid (3 days a week onsite & must be willing to relocate and ... Works closely with other technical and data analytics experts across the business to implement data ...

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Data Analytics Engineer information

See Philadelphia, PA salary details

$44.9K

$130.9K

$179.1K

How much do data analytics engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for data analytics engineer in Philadelphia, PA is $130,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,500.00 and $138,700.00 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 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:

Infographic showing various Data Analytics Engineer job openings in Philadelphia, PA as of August 2026, with employment types broken down into 81% Full Time, and 19% Contract. Highlights an 74% In-person, 13% Hybrid, and 13% Remote job distribution, with an average salary of $130,895 per year, or $62.9 per hour.

Sr. Data Analytics Engineer - Internal Audit

Vangard, Inc.

Malvern, PA

$112K - $134K/yr

Full-time

Posted 5 days ago


Job description

Vanguard's Internal Audit & SOX (IAS) department has an exciting opportunity in our Automation and Analytics team. We're looking for a tech-savvy, innovative individual who's passionate about building scalable data solutions and engineering robust analytics infrastructure. This role is a crucial part of our forward-thinking, dynamic team and is key to delivering automated utilities and data pipelines that provide greater assurance to the organization, increase stakeholder productivity, and deliver deeper insights into the operating effectiveness of our control environment-all of which ultimately support Vanguard's purpose: to take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.

You'll collaborate with a diverse and talented team of centralized and decentralized data analysts, and work closely with our analytics infrastructure and solutions using the latest technologies. The ideal candidate will have a strong background in data engineering, technical communication, and automation development, with hands-on experience in System frontend development, Streamlit, cloud platforms, Python, and data pipeline design.

Responsibilities:

  • Data Engineering & Pipeline Development: Design, build, and maintain scalable data pipelines and ETL processes to support analytics and automation initiatives. Ensure data quality, integrity, and performance across systems.
  • Requirements Gathering and Technical Design: Partner with stakeholders to translate business needs into technical specifications. Design data models, process flows, and system integrations aligned with strategic objectives.
  • Automation Development: Develop and deploy automation tools and scripts (e.g., Python, SQL, Power Apps) to streamline audit and business processes, improve efficiency, and reduce manual effort.
  • Data Visualization: Support the development of reporting front-end interfaces using tools such as Streamlit, hosted on AWS infrastructure. Collaborate with analytics and audit teams to design user-friendly applications that deliver insights and enable interaction with automated utilities and data pipelines.
  • Infrastructure & Systems Integration: Collaborate with IT and analytics teams to implement integrated solutions using cloud platforms (e.g., AWS), databases (e.g., SQL Server), and identity systems (e.g., Active Directory).
  • Process Optimization: Identify and implement opportunities for process improvement through automation and data-driven insights within internal audit workflows.
  • Innovation & Technology Adoption: Stay current with emerging technologies (e.g., GenAI, RPA, AI/ML) and recommend innovative solutions that align with organizational strategies.

What It Takes:

  • Proficiency inPython,SQL, and data engineering tools and frameworks.
  • Experience withdata visualization platforms(e.g., Tableau, Power BI),cloud infrastructure(e.g., AWS), anddatabase systems(e.g., SQL Server).
  • Familiarity withRPA,AI/ML concepts, and modern data architecture.
  • Strong communication skills to bridge technical and non-technical stakeholders.
  • Ability to thrive in a fast-paced, ambiguous environment and manage multiple priorities.
  • Strong planning and organizational skills with a focus on execution and delivery.

Qualifications:

  • Minimum of 5 years related technical experience; some working knowledge of audit, risk, and controls.
  • Undergraduate degree in a related field or the equivalent combination of training and experience (e.g., MIS, Information Technology, Data Sciences, Data / Business Analytics).

Special factor:

  • This is a hybrid role - candidates must be commutable to Vanguard's Malvern, PA office.

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission-we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.