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Python Data Developer Jobs in Missouri (NOW HIRING)

Data Engineer

Kansas City, MO · On-site

$111K - $134K/yr

... Python strongly preferred) for pipeline development, data validation, and operational tooling. • Cloud data platform experience (AWS or GCP), including managed warehouses (Databricks and Snowflake ...

Data Engineer III

Saint Louis, MO · On-site

$111K - $133K/yr

Proficient in programming languages such as Python and SQL for database querying and manipulation. * Strong understanding of AWS services related to data engineering, such as Amazon S3, Amazon ...

Data Engineer III

Saint Louis, MO · On-site

$111K - $133K/yr

Proficient in programming languages such as Python and SQL for database querying and manipulation. * Strong understanding of AWS services related to data engineering, such as Amazon S3, Amazon ...

Data Engineer (MedInsight)

Saint Louis, MO · On-site +1

$93K - $177K/yr

MedInsight's engineering team is building the next generation of healthcare data analytics. We are ... Analyze and improve data intake processes and optimize SparkSQL/Python workloads for performance ...

Data Engineer (MedInsight)

Saint Louis, MO · On-site +1

$93K - $177K/yr

MedInsight's engineering team is building the next generation of healthcare data analytics. We are ... Analyze and improve data intake processes and optimize SparkSQL/Python workloads for performance ...

At Walmart, we prioritize innovation and data security. Our team is dedicated to maintaining a ... Expert skills in programming languages such as Java or Python and in interfacing with a backend ...

Data Bricks Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

... Python and PySpark. • Advanced proficiency writing SQL for analytics and ETL processes. • ... DevOps for CI/CD and source control workflows. • Strong analytical, problem-solving, and ...

At Walmart, we prioritize innovation and data security. Our team is dedicated to maintaining a ... Expert skills in programming languages such as Java or Python and in interfacing with a backend ...

At Walmart, we prioritize innovation and data security. Our team is dedicated to maintaining a ... Expert skills in programming languages such as Java or Python and in interfacing with a backend ...

... Engineering. What the client is really looking for: * Advanced SQL + Python (core requirement); Joins, CTEs, window functions, analytical queries * Hands-on with data quality, validation, and ...

Data Scientist

Saint Louis, MO · Remote

$55 - $60/hr

... Engineering. What the client is really looking for: * Advanced SQL + Python (core requirement); Joins, CTEs, window functions, analytical queries * Hands-on with data quality, validation, and ...

Data Engineer - Multiple Positions

Chesterfield, MO · On-site

$113K - $136K/yr

... and DevOps practices within data environments to optimize development and deployment workflows. * Technical Skills: * Expert-level proficiency in Spark Scala, Python, and PySpark. * In-depth ...

Big Data Engineer

Creve Coeur, MO · On-site

$52.25 - $69/hr

General Purpose Programming languages (Java, C, Scala, Python, Erlang, etc.) * Database Technology ... Data lakes * Experience with cloud big data technology (AWS Data Pipeline, GCP DataFlow, Azure ...

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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 Missouri? For Python Data Developer jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Python Data Developer jobs in Missouri look for? The top searched job categories for Python Data Developer jobs in Missouri are:

$111K - $134K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Job Summary:
MFour is a leading consumer intelligence platform transforming how businesses understand consumers through validated data. They are seeking a Senior Data Engineer to own the consumer-data pipeline, responsible for ingesting and unifying behavioral data into a reliable identity graph that supports their AI-driven solutions.
Responsibilities:
• Own MFour's consumer-data pipeline — the core engine behind insights hundreds of leading brands rely on.
• Solve a genuinely hard problem: unifying real-time app, web, purchase, ChatGPT, and foot-traffic data into one coherent identity graph.
• Sit at the center of the platform — your pipeline feeds DANI's AI query layer and every customer-facing product.
• Build something that compounds: every improvement makes DANI smarter and every downstream team faster.
• Work directly alongside the Principal Platform Engineer and across all product teams.
• Own the end-to-end, multi-source pipeline: ingest, transformation, cleaning, and delivery.
• Enforce data-quality standards at ingest — catch schema drift, anomalies, and source failures before they hit downstream systems.
• Keep the pipeline fast, scalable, and reliable for a live AI query layer, owning SLAs when upstream sources change.
• Own the identity-resolution system that merges behavioral signals into a clean, deduplicated identity graph — the foundation DANI queries against.
• Build and refine entity-matching, dedup, and merge logic that resolves conflicting signals, with clear confidence rules.
• Partner with the Principal Platform Engineer to optimize data structures and access patterns for DANI — low-latency, high-fidelity, queryable.
• Provide freshness and availability guarantees for Survey and Research fulfillment, backed by defined data contracts.
• Build monitoring and alerting across the pipeline (freshness, volume anomalies, schema violations, identity drift) so issues surface in minutes, not days.
• Own root-cause analysis for incidents — trace failures to the source, document the fix, and harden against recurrence.
• Proactively retire technical debt before it becomes a risk.
• Enforce data-handling practices that keep behavioral data compliant with MFour's privacy commitments and applicable regulations.
• Maintain clear data lineage and retention policies that satisfy internal audits and enterprise-client trust.
• Deliver data to Survey and Research fulfillment teams that's available, correctly structured, and on time — with clear ownership when it's not.
• Partner with the Product Pod to surface data constraints that shape what DANI can confidently answer.
• Document architecture, data contracts, and known failure modes so system knowledge isn't trapped in one person's head.
Qualifications:
Required:
• 5+ years of data engineering experience with clear ownership of production pipelines — not just contribution to them. You have shipped and operated multi-source data systems at scale.
• Deep expertise in batch and streaming data pipeline architectures — ingest, transformation, deduplication, and delivery — using tools such as Apache Spark, Kafka, Flink, dbt, Airflow, or equivalents.
• Hands-on experience with entity resolution, identity matching, or record linkage across multiple data sources — including the hard cases: conflicting signals, sparse data, and evolving schemas.
• Strong command of SQL and at least one general-purpose language (Python strongly preferred) for pipeline development, data validation, and operational tooling.
• Cloud data platform experience (AWS or GCP), including managed warehouses (Databricks and Snowflake), object storage, and cloud-native orchestration services.
• A rigorous approach to data quality: you define what 'clean' means, you build validation into the pipeline, and you treat a silent data error as seriously as a system outage.
• Familiarity with consumer data privacy requirements (CCPA, CPRA) and the practical implications for how behavioral data is collected, stored, and processed in a commercial research context.
Company:
Delivering validated consumer intelligence that brands can trust. Founded in 2001, the company is headquartered in Irvine, USA, with a team of 51-200 employees. The company is currently Growth Stage.