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Big Data Developer Jobs in Pittsburgh, PA (NOW HIRING)

ExlService Holdings, Inc.

Big Data Engineer

Pittsburgh, PA · On-site

$100K - $130K/yr

Big Data Engineer Summary We are looking for an experienced Big Data Engineer with 7-10 years of hands-on experience to design, build, and maintain scalable data pipelines and processing systems in ...

ExlService Holdings, Inc.

Big Data Engineer

Pittsburgh, PA · On-site

$54 - $71.50/hr

Big Data Engineer Summary We are looking for an experienced Big Data Engineer with 7-10 years of hands-on experience to design, build, and maintain scalable data pipelines and processing systems in ...

CGI Inc.

Kafka/Spark Developer

Pittsburgh, PA · On-site

As Kafka Spark Software developers, you will be responsible for developing and maintaining scalable big data solutions using Hadoop, Spark, Kafka, and Impala to support enterprise data processing and ...

CGI

Kafka/Spark Developer

Pittsburgh, PA · On-site

As Kafka Spark Software developers, you will be responsible for developing and maintaining scalable big data solutions using Hadoop, Spark, Kafka, and Impala to support enterprise data processing and ...

CYNET SYSTEMS

Application Developer II

Pittsburgh, PA · On-site

$51 - $60/hr

Experience working in a Big Data environment within GCP. * Experience with Google Cloud Storage ... Data Engineering. * Data Pipeline. * BigQuery. * Python. * Cloud Run. * GCP Security. * Big Data.

UPMC Enterprises

Data Engineer, Senior

Pittsburgh, PA · On-site

$102K - $139K/yr

Build relationships across the One-Enterprises organization, developing awareness of big picture ... Data Engineering team and across the broader UPMC Enterprises team. * Objectively assess and sign ...

kWantera

Energy Data Analyst

Pittsburgh, PA · On-site

The ideal candidate is experienced and comfortable with analyzing big data and crunching numbers, is familiar with the electricity wholesale markets in the US, and has programming background ...

kWantera

Energy Data Analyst

Pittsburgh, PA

The ideal candidate is experienced and comfortable with analyzing big data and crunching numbers, is familiar with the electricity wholesale markets in the US, and has programming background ...

CGI

Data Engineer

Pittsburgh, PA · On-site

$107K - $128K/yr

Support analytics reporting and risk platforms Requirements: . 6+ years of experience in data engineering and big data processing . Strong expertise in Apache Spark (Spark Core, Spark SQL) and ...

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Big Data Developer information

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$55

$72

How much do big data developer jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for big data developer in Pittsburgh, PA is $55.12, according to ZipRecruiter salary data. Most workers in this role earn between $47.60 and $61.78 per hour, depending on experience, location, and employer.

What is a big data developer?

A big data developer, sometimes called a big data engineer, creates technical tools and systems that allow an organization to integrate data analytics seamlessly into business solutions. As a big data developer, your primary duties include designing, coding, testing, and monitoring software and applications that are used to achieve your organization’s goals. Big data developers work in a variety of fields, including health care, finance, biotech, media, and advertising, as well as within various government departments. The job typically involves working as part of a large team of developers, data science specialists, and programmers.

What is a big data developer?

A Big Data Developer is a technology professional who designs, builds, and maintains systems and applications for processing and analyzing large volumes of data. They work with big data tools and frameworks like Hadoop, Spark, and NoSQL databases to manage data pipelines and ensure efficient data storage and retrieval. Their role often involves collaborating with data scientists and analysts to turn massive, complex data sets into actionable insights for organizations.

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

To thrive as a Big Data Developer, you need strong programming skills (such as Java, Scala, or Python), a deep understanding of data structures, and experience with distributed systems, often supported by a bachelor’s degree in computer science or a related field. Proficiency with big data tools and platforms like Hadoop, Spark, Hive, Kafka, and NoSQL databases, as well as familiarity with cloud services (AWS, Azure, or Google Cloud), is typically required. Analytical thinking, problem-solving abilities, and effective communication help developers collaborate with cross-functional teams and translate business needs into technical solutions. These skills are crucial for efficiently processing and analyzing large-scale data to drive informed decision-making and innovation.

What are some common challenges big data developers face when integrating new data sources into existing pipelines?

A common challenge for Big Data Developers is ensuring compatibility and data quality when integrating new data sources into established pipelines. This often involves handling different data formats, managing schema evolution, and addressing inconsistencies or missing data. Developers must also optimize for performance, as adding new sources can impact processing speed and resource utilization. Close collaboration with data engineers, analysts, and business stakeholders is essential to ensure that the integrated data supports organizational goals and maintains high reliability.

What is the difference between Big Data Developer vs Data Engineer?

AspectBig Data DeveloperData Engineer
Primary FocusDesigning and developing big data applications and solutionsBuilding and maintaining data pipelines and infrastructure
Skills & CertificationsHadoop, Spark, Java, Scala, SQLETL, cloud platforms, scripting, database management
Work EnvironmentData teams, software development projectsData infrastructure, cloud environments, data warehouses
Industry UsageTech, finance, healthcare, retailTech, finance, telecom, e-commerce

While both roles work with big data technologies, Big Data Developers focus on creating applications and solutions for processing large datasets, whereas Data Engineers build and maintain the data infrastructure that supports these applications. Understanding these distinctions helps in choosing the right career path or job search focus.

More about Big Data Developer jobs
Big Data Developer jobs near you
Infographic showing various Big Data Developer job openings in Pittsburgh, PA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $114,660 per year, or $55.1 per hour.

Big Data Engineer

ExlService Holdings, Inc.

Pittsburgh, PA • On-site

$100K - $130K/yr

Full-time

Posted 17 days ago

ExlService Holdings rating

7.8

Company rating: 7.8 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

135th of 495 rated business services

Job description


Job Description: Big Data Engineer Summary
We are looking for an experienced Big Data Engineer with 7-10 years of hands-on experience to design, build, and maintain scalable data pipelines and processing systems in an on-premises Big Data environment. Beyond strong individual contribution, the ideal candidate will own architecture and design decisions, set technical direction, and mentor and support other developers on the team. The role works closely with cross-functional teams to deliver reliable, high-quality data solutions that support business and analytics needs.
Roles & Responsibilities
  • Lead the design, development, and maintenance of robust, scalable data pipelines for ingestion, transformation, and processing of large datasets in an on-premises environment.
  • Own architectural and design decisions for data solutions, evaluating trade-offs and defining technical standards for the team.
  • Mentor, guide, and support other data engineers through code reviews, design reviews, technical coaching, and hands-on problem-solving.
  • Build and optimize data workflows using Python, Spark, and the Hadoop ecosystem.
  • Work extensively with Hadoop ecosystem components (Hive, HDFS, Impala) to manage and query large-scale data.
  • Manage and optimize batch scheduling and job orchestration using enterprise schedulers such as CA7 or Control-M.
  • Ensure data quality, integrity, and performance across data platforms.
  • Collaborate with data analysts, data scientists, and business stakeholders to translate data requirements into sound technical designs.
  • Troubleshoot and resolve complex issues in data pipelines and production environments, acting as an escalation point for the team.
  • Champion best practices for coding standards, version control, testing, and documentation.
  • Stay current with emerging technologies, particularly AI/ML capabilities, and identify opportunities to apply them to data engineering workflows.

Technical Skills Must Have
  • 7-10 years of overall experience in data engineering, with a proven track record in technical leadership (design ownership, mentoring, guiding development teams).
  • Python - strong hands-on development experience building production-grade data solutions.
  • Big Data / Hadoop ecosystem (Hadoop, Hive, Impala, HDFS) - deep, hands-on experience in on-premises environments.
  • Apache Spark - solid experience developing and tuning large-scale distributed data processing jobs.
  • Job scheduling / orchestration - hands-on experience with CA7 or Control-M (or comparable enterprise schedulers).
  • Strong understanding of data structures, ETL processes, and SQL.
  • Extensive experience with large-scale data processing and distributed systems.
  • Demonstrated ability to make sound architecture/design decisions and to mentor and support other developers.
  • Exposure to AI/ML concepts or tools, with a strong willingness to learn and grow in this space.

Responsibilities
Roles & Responsibilities
  • Lead the design, development, and maintenance of robust, scalable data pipelines for ingestion, transformation, and processing of large datasets in an on-premises environment.
  • Own architectural and design decisions for data solutions, evaluating trade-offs and defining technical standards for the team.
  • Mentor, guide, and support other data engineers through code reviews, design reviews, technical coaching, and hands-on problem-solving.
  • Build and optimize data workflows using Python, Spark, and the Hadoop ecosystem.
  • Work extensively with Hadoop ecosystem components (Hive, HDFS, Impala) to manage and query large-scale data.
  • Manage and optimize batch scheduling and job orchestration using enterprise schedulers such as CA7 or Control-M.
  • Ensure data quality, integrity, and performance across data platforms.
  • Collaborate with data analysts, data scientists, and business stakeholders to translate data requirements into sound technical designs.
  • Troubleshoot and resolve complex issues in data pipelines and production environments, acting as an escalation point for the team.
  • Champion best practices for coding standards, version control, testing, and documentation.
  • Stay current with emerging technologies, particularly AI/ML capabilities, and identify opportunities to apply them to data engineering workflows.

Qualifications
  • 7-10 years of overall experience in data engineering, with a proven track record in technical leadership (design ownership, mentoring, guiding development teams).
  • Python - strong hands-on development experience building production-grade data solutions.
  • Big Data / Hadoop ecosystem (Hadoop, Hive, Impala, HDFS) - deep, hands-on experience in on-premises environments.
  • Base Compensation Range: $100,000- $130,000
  • The posted range is the hiring range for this role - a subset of the broader range available to employees over time - and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.

About Us
EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world's leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.
EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL's Human Resources team, as well as our hiring managers.
About the Team
EXL is the indispensable partner for leading businesses in data-led industries such as insurance, banking and financial services, healthcare, retail and logistics. We bring a unique combination of data, advanced analytics, digital technology and industry expertise to help our clients turn data into insights, streamline operations, improve customer experience, and transform their business. Our partnerships with clients are built on a foundation of collaboration - and we've been chosen as a partner by nine of the top ten leading US insurance companies, nine of the top 20 global banks, and six of the top ten US health care payers. We function as one team to make your goals our goals, whether that's unlocking the value of generative AI or embedding analytics into workflows that reduce risk or power your growth. Clients choose EXL as their transformation partner for many reasons. Our geographic diversity make talent all over the world instantly accessible. Digital accelerators enable unmatched speed-to-value, letting you realize results fast. It's our people that truly set us apart, though, including the 1,500 data scientists we have dedicated to our generative AI practice. And our more than twenty years of experience in delivering business services, garnering stellar client references, and maintaining a solid balance sheet are reassuring to our C-suite clients. Find out for yourself why clients, employees, and analysts think we're some of the best in the business. Contact us to see how we can help you achieve your goals.

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