Data and Automation Engineer - Onsite

Hello,

My name is Pavan and I am a Talent Acquisition Specialist at Park Computer Systems, Inc., a Technology Consulting and Staffing company. After reviewing your resume, I believe that you may be a good fit for a job opening with one of our clients. The highlights of the position are:

Job Title: Data and Automation Engineer

Location: Milpitas, CA 95035 (5 Days Onsite)

Duration: 04-06 Months Contract

Job Description:

About the Role

Client is seeking a Data and Automation Engineer to build, migrate, test, and operate production data jobs and automated workflows. The role will also support financial and transactional data analysis, reconciliation, and reporting using SQL, Snowflake, Python, and Excel.

The ideal candidate will have 5 7 years of experience building and supporting production data processing and automation solutions and will be highly proficient in Python, SQL, and Snowflake. This person should also have experience working with large transactional datasets, data validation, reconciliation, exception analysis, and automation of recurring business processes.

A key responsibility of this role will be to design, develop, refactor, test, and review production Python code while modernizing manual workflows into reliable, maintainable, scheduled, monitored, and supportable automated solutions. The person will work closely with Accounting, Data, Engineering, Operations, and DevOps teams to improve process efficiency, data accuracy, reliability, and operational controls.

Key Responsibilities

• Extract, analyze, validate, and manage large financial and transactional datasets using SQL, Snowflake, Python, and Excel.
• Develop and optimize complex SQL queries for reporting, reconciliation, transaction analysis, and data-quality validation.
• Perform and automate financial and transactional reconciliations, and investigate breaks such as unmatched records, duplicates, timing differences, missing data, and incorrect mappings.
• Design, develop, refactor, test, and review production Python code used for data processing, reconciliation, integrations, and automation.
• Migrate Python jobs and manual or spreadsheet-based workflows to the company s production job orchestration platform, ensuring appropriate scheduling, monitoring, alerting, error handling, retries, and operational support.
• Support period-end close, reporting, audit requests, and resolution of data discrepancies.
• Document SQL logic, Python code, reconciliation rules, data mappings, workflows, and support procedures.
• Collaborate with Accounting, Data, Engineering, Operations, and DevOps while following company standards for security, testing, change management, and auditability.

Required Qualifications

• Bachelor s degree in Computer Science, Information Systems, Data Analytics, or a related field, or equivalent practical experience.
• 5 7 years of experience in software engineering, data engineering, automation engineering, or related roles involving production data processing and workflow
• Strong Python experience developing and supporting production-grade data processing, automation, file-handling, and integration solutions.
• Strong SQL skills, including complex joins, CTEs, window functions, aggregations, and data-validation queries.
• Hands-on experience with Snowflake or a comparable data platform.
• Experience with financial or transactional reconciliation and investigating data discrepancies across multiple systems.
• Experience with Git, testing, code reviews, source control, and CI/CD practices.
• Strong analytical, problem-solving, documentation, and communication skills, with proficiency in Excel for validation and operational analysis.

Preferred Qualifications

• Experience in fintech, payments, banking, payroll, or another transaction-intensive environment, with an understanding of basic accounting concepts.
• Experience working with APIs, SFTP, CSV, JSON, Excel, fixed-width files, and third-party integrations.
• Familiarity with Sigma Computing, Power BI, Tableau, Looker, or similar reporting tools.

Success Measures

• Reliability and operational stability of production data jobs, including monitoring, alerting, and failure recovery.
• Improved code quality, maintainability, testability, and supportability of automated workflows.
• Improved accuracy and timeliness of reconciliations, with fewer recurring data-quality issues and exceptions.
• Reduction in manual spreadsheet work and repetitive processing through successful automation.
• Faster investigation and resolution of data discrepancies.

If you believe that you are well qualified for this position and are currently in the job market, or interested in making a change, please do give me a call at - Ext 241 or reply to this email. When responding, please include your direct phone number, so that I may revert back to you promptly.

If this is your first exposure to Park Computer Systems, you can check us out at http:

Thank you for your time, and looking forward to a timely response from you.