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Senior Python Automation Jobs in Georgia (NOW HIRING)

Mainframe Python

Atlanta, GA

$47 - $60.50/hr

Position: Senior Python Engineer -- Mainframe (DB2/JCL) Location: Atlanta, GA (Onsite) Senior ... Job submission & automation: Submit and monitor jobs via SDSF, z/OSMF REST APIs, or Zowe CLI; parse ...

New

Senior Automation Engineer

Atlanta, GA · Hybrid

$100K - $131K/yr

Design, build, and maintain scalable Python-based automation frameworks and scripts from the ground ... As an experienced Senior Automation Engineer ,you will have the ability to share new ideas and ...

New

Work closely with network architects, senior management and operations teams. * Act as an ... Hands-on experience with automation and scripting tools (e.g., Python, Ansible, RESTful APIs)

Automation Tester/SDET

Savannah, GA · On-site

$42.75 - $56.50/hr

Python, Rest API, LLM / AI * 3+ years Exp Role 3 : Automation Tester Location : Alpharetta, GA ... Java, Selenium & Playwright ,API testing, Agile, Jira * 3+ years Exp Thanks & Regards | Senior ...

Senior Backend Developer (Cloud Automation)

Suwanee, GA · On-site

$112K - $145K/yr

We are seeking a Sr. Backend Developer Cloud Automation to join our team. The USA is a Senior ... Design and develop cloud-native applications in Go, Python, and C++; drive language selection based ...

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Senior Python Automation information

How much does a senior Python developer make?

A senior Python developer typically earns between $100,000 and $150,000 annually, depending on experience, location, and industry. They often have expertise in frameworks like Django or Flask and may hold certifications or advanced degrees that influence salary levels.

What is the highest paying job in Python?

The highest paying Python-related roles are often senior positions such as Lead Data Scientist, Machine Learning Engineer, or Quantitative Developer, which require advanced skills in algorithms, statistics, and large-scale data processing. These roles typically offer salaries exceeding $150,000 annually, especially in finance, technology, and research sectors, and often require expertise in frameworks like TensorFlow or PyTorch and strong programming experience.

What kind of jobs use Python automation?

Senior Python Automation roles are common in fields such as software development, data analysis, quality assurance, and IT operations. These jobs involve creating scripts and tools to automate repetitive tasks, improve efficiency, and manage systems, often requiring knowledge of frameworks like Selenium or libraries such as Pandas. Python automation is valuable in environments that prioritize process optimization and scalable solutions.

How much does it automation with Python pay?

Senior Python Automation roles typically offer salaries ranging from $80,000 to $130,000 annually, depending on experience, location, and industry. Professionals with strong scripting skills, knowledge of automation tools, and certifications can command higher compensation. Entry-level positions may start lower, while experienced developers in high-demand areas can earn more.
What are the most commonly searched types of Python Automation jobs in Georgia? The most popular types of Python Automation jobs in Georgia are:

Python Engineer with Mainframe, Atlanta GA

Calabitek

Atlanta, GA

$48.25 - $66.50/hr

Other

Posted yesterday


Job description

Senior Python Engineer - Mainframe (DB2/JCL),
Atlanta, GA
Onsite

Senior Python Engineer - Mainframe (DB2/JCL) Design & build Python on z/OS (USS): Develop CLI tools, services, and batch utilities that run natively on z/OS Unix System Services (USS) or orchestrate mainframe jobs from distributed hosts. Batch orchestration: Create and maintain JCL (PROCs, symbolics, condition codes, GDGs) and integrate with enterprise schedulers (e.g., Control-M, CA-7). Implement robust restart/recovery and step-level error handling. DB2 for z/OS engineering: Write and tune SQL; implement stored procedures; design schemas and indexes; use EXPLAIN, RUNSTATS, and utilities (LOAD/UNLOAD/REORG) to hit SLAs. Python DB2 integration: Connect via ibm_db/CLI/ODBC and optimize connection pooling, cursor usage, and transaction boundaries for high-throughput workloads. Data processing pipelines (plus): Build high-volume ETL/ELT flows with Python (e.g., pandas, PyArrow, Dask) and efficient I/O (binary formats, streaming, chunking). Job submission & automation: Submit and monitor jobs via SDSF, z/OSMF REST APIs, or Zowe CLI; parse JES output; automate handoffs and notifications. Reliability & observability: Implement structured logging, metrics, and tracing; integrate with enterprise monitoring (e.g., Splunk, ELK). Testing & CI/CD: Enforce unit/integration tests (pytest), code reviews, linting/type hints (flake8/ruff/mypy), packaging, and CI/CD (e.g., Jenkins, GitLab). Security & compliance: Follow RACF/Top Secret/ACF2 controls, least privilege, and data governance for PII/PCI/SOX environments. Mentorship & documentation: Coach engineers on Python + mainframe best practices; produce clear runbooks and architecture docs. Required qualifications 8+ years professional Python (3.x) building reliable, performant production systems (CLIs, services, or batch). Hands-on Python on the mainframe (must-have): Comfortable with z/OS USS, TSO/ISPF, SDSF, OMVS, dataset concepts (PS/PO, GDGs), code pages/EBCDIC vs ASCII, and file I/O nuances. Mainframe DB2 expertise: Strong DB2 for z/OS (SQL tuning, indexing strategies, access paths, utilities, locking & concurrency). Familiar with SPUFI, DSNTEP2, IBM Data Studio (or equivalents). Deep JCL proficiency: PROCs, symbolic parms, condition codes, dataset allocation, DFSORT/ICETOOL, IDCAMS, and common utilities; experience wiring JCL into enterprise schedulers. Scripting & OS: Shell (sh/bash) on USS; comfort with dataset/file conversions, large file throughput, and job logs. SDLC discipline: Git, trunk-based development, code reviews, tickets/change management (e.g., Jira/ServiceNow). Excellent communicator with the ability to translate between mainframe, data, and app teams. Nice-to-have (strong plus) Data-processing Python: pandas, PyArrow, Dask; memory/perf tuning for large datasets; binary formats (Parquet/Avro). Automation toolchain: Zowe CLI, z/OSMF REST, IBM Z Open Automation Utilities, Ansible for z/OS. Integration: IBM MQ, CICS, Kafka/CDC (e.g., IBM Data Replication), REST/gRPC services bridging z/OS and distributed. Performance engineering: SMF insights, buffer pool tuning (with DBAs), batch window optimization. Refactoring legacy: Translating COBOL/PL/I batch logic to Python where appropriate; creating safe migration paths. Distributed data engines: PySpark/Spark (for off-platform processing), Airflow. Observability & SRE: SLA/SLO design, incident response for nightly/weekly batch cycles. Tools & environment (illustrative) Mainframe: IBM z/OS 2.x, USS, TSO/ISPF, SDSF, RACF/Top Secret/ACF2 Data: DB2 12/13 for z/OS; utilities (REORG/RUNSTATS/LOAD/UNLOAD) Python: 3.x, venv/poetry, ibm_db/ODBC, requests, pandas/PyArrow (as applicable) Automation: Zowe CLI, z/OSMF APIs, Control-M/CA-7, Jenkins/GitLab CI Monitoring: Splunk/ELK, enterprise log aggregation Success metrics Batch SLAs consistently met; reduced average job elapsed time and rerun rates Measurable DB2 query/perf improvements (e.g., CPU, getpages, elapsed time) Increased automation coverage (job submission/monitoring, recovery) High test coverage and low change-failure rate across releases Education & certification BS/MS in CS, EE, or equivalent experience Nice-to-have: IBM Certified Database Admin - DB2 for z/OS; IBM z/OS Associate/Professional; Control-M/CA-7 certifications