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Python Data Developer Jobs in Pennsylvania (NOW HIRING)

SANS

Python Data Engineer

Philadelphia, PA · On-site

The consultant works onsite as part of the client's data engineering effort, integrating the client ... Write production-grade Python for data processing and integration between on-prem and cloud systems.

New

Dlapiper

Data Engineer

Philadelphia, PA · On-site

$115K - $138K/yr

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Proficiency in SQL and Python. * Data pipeline tooling and cloud data services experience (Azure ...

Sarian, Inc.

Python Developer

Pittsburgh, PA · On-site

$48.75 - $67.25/hr

Python Developer Location: Pittsburgh Fulltime position Onsite position JD: * 8-12 years of ... Data Analysis/Machine Learning. * Testing/Debugging/Security. * Writing, testing, and debugging ...

Marencor

Python/AI/ML Engineer

Malvern, PA · On-site

... developer with a year or two experience with generative AI (genAI is only a few years old from the ... Collaborate with data scientists, product managers, and other stakeholders to understand ...

RIT Solutions, Inc.

Senior Data Engineer -

Malvern, PA · On-site

$112K - $134K/yr

... Python developer Qualifications : Required : • Minimum 8-10 years of experience • Role - Level 4 Big Data Engineer, Python developer • Required skillset - Python • Required skillset - SQL • ...

EXL

Data Engineer

Pittsburgh, PA

$100/hr

... Python and SQL , along with hands-on experience in DevOps and CI/CD practices . The role involves building scalable data pipelines, optimizing data systems, and enabling efficient data-driven ...

Data Ideology

Sr. Data Engineer (Snowflake)

Pittsburgh, PA · Remote

$111K - $133K/yr

Develop and optimize data pipelines using tools such as dbt, Python, CloverDX, and cloud-native ... Mentor junior engineers and support knowledge sharing across the team. Supervisory Responsibilities:

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Python Data Developer information

What are some common challenges faced by Python Data Developers when working with large datasets?

Python Data Developers often encounter challenges related to efficiently processing and managing large datasets, such as optimizing data pipelines for speed and memory usage. Handling data quality issues, integrating data from multiple sources, and ensuring scalability of their solutions are also frequent hurdles. Collaboration with data engineers, analysts, and stakeholders is crucial for understanding requirements and delivering robust results. Staying up to date with the latest libraries and tools, like Pandas, Dask, or PySpark, is also important to overcome these challenges and maintain high performance.

What is the difference between Python Data Developer vs Data Analyst?

AspectPython Data DeveloperData Analyst
Required SkillsPython, SQL, data modeling, ETL processesExcel, SQL, data visualization, basic statistics
CertificationsPython certifications, data engineering coursesData analysis certifications, Excel certifications
Work EnvironmentData engineering teams, software development projectsBusiness units, reporting teams
Industry UsageTech, finance, healthcare, where data pipelines are neededMarketing, finance, operations for insights and reporting

The Python Data Developer focuses on building data pipelines, integrating data sources, and developing scalable data solutions using Python. In contrast, Data Analysts primarily interpret data, create reports, and provide insights for decision-making. While both roles require SQL and data handling skills, Python Data Developers are more involved in data engineering tasks, whereas Data Analysts focus on data visualization and analysis.

What are Python Data Developers?

Python Data Developers are professionals who use the Python programming language to collect, process, and analyze data. They build and maintain data pipelines, write scripts for data manipulation, and work with databases to ensure data is accessible and usable for analytics and business insights. These developers often collaborate with data scientists, analysts, and other IT professionals to support data-driven decision-making within an organization.

What are the key skills and qualifications needed to thrive as a Python Data Developer, and why are they important?

To excel as a Python Data Developer, you need strong programming skills in Python, a solid understanding of data structures, algorithms, and experience with relational and NoSQL databases. Familiarity with data processing libraries (like Pandas, NumPy), ETL tools, and version control systems, as well as knowledge of cloud platforms (such as AWS or Azure), are typically required. Problem-solving ability, attention to detail, and effective communication are vital soft skills in this role. These skills enable efficient data pipeline development, ensure data quality, and facilitate collaboration within technical teams.
What are popular job titles related to Python Data Developer jobs in Pennsylvania? For Python Data Developer jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Python Data Developer jobs in Pennsylvania look for? The top searched job categories for Python Data Developer jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Python Data Developer jobs? Cities in Pennsylvania with the most Python Data Developer job openings:
Python Data Developer jobs near you

Python Data Engineer

SANS

Philadelphia, PA • On-site

Other

Posted 2 days ago

New

Job description


Client is placing a senior data integration consultant embedded at a financial services client. The consultant works onsite as part of the client's data engineering effort, integrating the client's systems and data sources with Client's Declarative Agentic Framework (DAF) and connected products.
This is delivery work, not advisory. The consultant owns the data pipelines, warehouse structures, and integration points that the deployment depends on, and is accountable for data quality and reliability in production.
What the Consultant Will Do

  • Design and build data integration pipelines connecting client source systems (reference data, pricing, transaction, custody, or similar) to client's AI's platform .
  • Own data warehouse and data lake architecture for the engagement, including ingestion, transformation, and data quality rules.
  • Work hands-on with ETL tooling (Informatica, Snowflake, or equivalent) and cloud data platforms (AWS or Azure).
  • Write production-grade Python for data processing and integration between on-prem and cloud systems.
  • Define data reconciliation and data lineage processes so the client can trust what the pipelines produce.
  • Coordinate with the client's data engineering, ops, and compliance stakeholders, and with client's AI's deployment team.
  • Document architecture decisions and integration patterns so the work is defensible and repeatable across future deployments.

Required Background

  • 10+ years in enterprise data architecture, data engineering, or solution architecture roles.
  • Direct experience in financial services, ideally capital markets, asset management, or securities operations. Candidate should recognize terms like reference data, corporate actions, and reconciliation without explanation.
  • Hands-on ETL and data warehousing expertise: Informatica, Snowflake , or comparable enterprise-grade tooling .
  • Production Python for data pipelines and integration work , not scripting on the side.
  • Experience with REST APIs, message queues (Kafka or similar), and containerized deployments (Docker).
  • Track record owning delivery end to end, from data analysis and architecture through production support, ideally with distributed or offshore team coordination.
  • Comfortable being the senior technical presence in the room with client stakeholders from day one. No ramp-up period.

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