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Python Data Developer Jobs in Mason, OH (NOW HIRING)

Associate Principal - Data Engineering

Cincinnati, OH ยท On-site

$109.90K - $132K/yr

Role description JD Developer Senior Developer PySpark Python Data Engineering Primary skills are pysparkpython Developer Location India Global Delivery Center Regional Hub Function Development ...

Programming experience on any standard data mining and modelling packages such as Python and R; and * Applying advanced statistical models and machine learning algorithms to develop and implement ...

... data structures, computer networking and operating systems Development expertise in REST/SOAP/JSON API Development expertise in message bus technologies such as RabbitMQ, ActiveMQ; Apache Kafka ...

Be Seen First

Our platform turns fragmented data into actionable insights, with privacy at its core. What You'll Build: * Scalable backend services in Python (FastAPI) and/or Node.js * Secure data ingestion ...

Python Tutor

Cincinnati, OH ยท Remote

$40/hr

Deep knowledge of Python syntax, data types, control flow, functions, object-oriented programming, file handling, modules and packages, list comprehensions, error handling, and popular libraries ...

Data Engineer II

Cincinnati, OH ยท On-site

$109.90K - $132K/yr

This is a junior-to-mid-level Data Engineer with BI experience, JavaScript, SQL, and Python. Job Summary Handle the design and construction of scalable data products, ensuring that all data systems ...

DATA ENGINEER IV

Cincinnati, OH ยท On-site

$68 - $70/hr

Data Engineer IV Location: Cincinnati, OH - onsite Payrate $70/hr on W2. USC and GC Holder ... Must Have Python SQL Nice To Have AWS Sagemaker DBT Snowflake What You'll Do Squad: Machine ...

Data Engineer II

Cincinnati, OH ยท On-site

$109.90K - $132K/yr

This is a junior-to-mid-level Data Engineer with BI experience, JavaScript, SQL, and Python. Job Summary : Handle the design and construction of scalable data products, ensuring that all data systems ...

Data Engineer Level 2

Cincinnati, OH ยท On-site

$55 - $70/hr

Data Engineer Level 2 Location: Blue Ash, OH 45241 Duration: 6 months (Contractor) Pay Rate: $55 ... Python, and cloud DataOps. You'll design scalable data pipelines, automate infrastructure with ...

Data Engineer

Kings Mills, OH ยท On-site

$107.50K - $129.10K/yr

Data Engineer The Data Engineer works within the ETL and Operations team to build high quality data ... Python scripting (PySpark, control scripts) * Architecting/designing data pipelines * Query and ...

Data Engineer

Cincinnati, OH ยท On-site

$109.90K - $132K/yr

Strong proficiency in Python. * Strong proficiency with Databricks and PySpark * Strong proficiency ... Strong proficiency with CI/CD pipelines and DevOps practices. * Strong understanding of data ...

Data Engineer

Cincinnati, OH ยท On-site

$109.90K - $132K/yr

Data Engineer Location: Cincinnati, OH (requires on-site work 5 days per week in downtown ... Kafka, IBM DataStage, Python * Financial or debit/transaction data experience * Prior work on data ...

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Python Data Developer information

See Mason, OH salary details

$12

$55

$81

How much do python data developer jobs pay per hour?

As of May 28, 2026, the average hourly pay for python data developer in Mason, OH is $55.13, according to ZipRecruiter salary data. Most workers in this role earn between $45.43 and $62.60 per hour, depending on experience, location, and employer.

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 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 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 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 popular job titles related to Python Data Developer jobs in Mason, OH? For Python Data Developer jobs in Mason, OH, the most frequently searched job titles are:
What job categories do people searching Python Data Developer jobs in Mason, OH look for? The top searched job categories for Python Data Developer jobs in Mason, OH are:
What cities near Mason, OH are hiring for Python Data Developer jobs? Cities near Mason, OH with the most Python Data Developer job openings:

Associate Principal - Data Engineering

LTM

Cincinnati, OH โ€ข On-site

$109.90K - $132K/yr

Other

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Role description
Job Description JD Developer Senior Developer PySpark Python Data Engineering
Primary skills are pysparkpython Developer
Location India Global Delivery Center Regional Hub
Function Development Services Data Engineering Analytics Digital Emerging Tech
Industry MultiNational FMCG
Cloud Strategy HyperscalerFirst AzureGCPAWS with Databricks Delta Lake
Level Developer Senior Developer
Key Responsibilities
PySpark Development Primary Focus
Design and develop productiongrade PySpark applications for largescale batch and streaming data processing
Implement advanced PySpark DataFrame API operations
oComplex transformations Window functions PivotUnpivot and nested struct handling
oMultidataset joins Broadcast joins SortMerge joins and skewhandling strategies
oCustom UDFs User Defined Functions and Pandas UDFs Vectorized UDFs for performancecritical transformations
oAggregations and GroupBy operations optimized for large FMCG datasets
Implement PySpark Structured Streaming for realtime data processing
oKafka Azure Event Hubs GCP PubSub as streaming sources
oWatermarking and windowing strategies for latearriving data
oStateful streaming operations using mapGroupsWithState
oExactlyonce and atleastonce delivery semantics
Apply advanced Spark Performance Tuning techniques
oPartition optimization repartition vs coalesce strategies
oHandling data skew using salting and custom partitioners
oBroadcast variable management and accumulator usage
oCatalyst optimizer hints and AQE Adaptive Query Execution tuning
oExecutor sizing memory fractions and parallelism configuration
Develop and maintain reusable PySpark libraries for shared data processing capabilities
Python Engineering Primary Focus
Build Pythonbased data services automation scripts and utility frameworks supporting the data platform
Develop REST API integrations using Python requests httpx for consuming SAP OData Salesforce and thirdparty FMCG APIs
Implement data validation and reconciliation frameworks using Python Great Expectations Pandera
Build Pythonbased orchestration scripts and helper utilities for Airflow DAGs and Databricks Workflows
Apply software engineering best practices
oUnit testing with pytest and integration testing with Testcontainers
oType hints docstrings and modular design patterns
oVirtual environments dependency management Poetrypip and packaging
Implement Pythonbased data quality checks Completeness consistency and conformity validations
Data Lakehouse Cloud Platform Primary Focus
Build and manage Data Lakehouse architectures on hyperscaler platforms
oAzure Databricks GCP Dataproc AWS EMR for Spark cluster management
oDelta Lake Apache Iceberg Apache Hudi for ACIDcompliant data lake storage
oMedallion Architecture BronzeSilverGold for progressive data refinement
Implement Delta Lake features
oACID transactions and schema enforcement
oTime Travel for data versioning and rollback
oDelta Live Tables DLT for declarative pipeline development
oOptimize and ZOrder for query performance acceleration
oChange Data Feed CDF for incremental data propagation
Manage Databricks Workflows and Job Clusters for production pipeline execution
Implement Databricks Auto Loader for incremental scalable data ingestion from cloud storage
Utilize Unity Catalog for data governance lineage and access control
Data Ingestion Integration
Build data ingestion pipelines from diverse FMCG data sources
oSAP S4HANA OData APIs BAPI extracts and IDocbased feeds
oSalesforce REST API Bulk API and Platform Events
oOperational Databases Oracle Cloud SQL Azure SQL and Cloud Spanner
oStreaming Sources Apache Kafka Azure Event Hubs and GCP PubSub
oFilebased Sources SFTP Azure Blob GCS and S3 CSV Parquet Avro JSON
Implement Change Data Capture CDC patterns for realtime database synchronization
Design schema evolution strategies to handle upstream data model changes gracefully
Publish processed data to downstream consumers
oBigQuery Azure Synapse Snowflake for BI and analytics
oFeature Stores FeastDatabricks for AIML model training
oPower BI Looker for business reporting
SQL Data Modeling
Write and optimize complex SQL queries for data extraction transformation and validation
Design data warehouse schemas Star and Snowflake models for FMCG analytics domains
Implement Spark SQL for largescale analytical query processing
Develop data quality SQL checks and reconciliation frameworks
Optimize SQL performance Query plans partition pruning and predicate pushdown