Senior Data Engineer

EPAM Systems; Argentina; Remote; ARS 2,000,000 - 6,000,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling & certifications

LinkedIn Learning access

Global career opportunities

Job summary

EPAM Systems Inc. is seeking a hands-on Senior Data Engineer to design, build, and support scalable data pipelines and cloud-based data solutions on AWS.

You will use Python, Pandas, and PySpark to process data, orchestrate workflows with MWAA/Airflow, and optimize queries with Athena. You will also automate infrastructure with Terraform and GitHub Actions, implement data quality controls, and collaborate in an Agile team to drive best practices across projects.

Qualifications

• A minimum of 3 years of professional data engineering experience.
• Strong Python and Pandas skills for data manipulation.
• Hands-on PySpark experience with large-scale data processing.
• Experience with AWS MWAA or Apache Airflow for workflows.
• Familiarity with Terraform and CI/CD tooling.
• GitHub Actions and DevOps practices in data environments.
• Upper-intermediate English proficiency (B1+).
• Nice to have Gen AI or finance industry exposure.

Responsibilities

• Design, build, and maintain scalable data pipelines on AWS.
• Develop data processing solutions using Python, Pandas, and PySpark.
• Orchestrate workflows with MWAA/Airflow to run pipelines reliably.
• Query data with AWS Athena for efficient analysis and reporting.
• Automate infrastructure with Terraform and GitHub Actions.
• Implement testing, monitoring, and data quality controls.
• Participate in code reviews and promote engineering best practices.

Skills

Python programming

Pandas

PySpark

DevOps practices

Agile/Scrum

English (B1+)

Tools

AWS

Airflow (MWAA)

Terraform

GitHub Actions

Athena

Job description

We are looking for a hands-on Senior Data Engineer to build and support scalable data pipelines and cloud-based data solutions. The ideal candidate will have strong experience in Python, PySpark, AWS, Airflow, and DevOps, with a focus on production-quality engineering and automationResponsibilitiesDesign, build, and maintain scalable data pipelines deployed on AWSDevelop robust data processing solutions using Python, Pandas, and PySparkBuild and manage workflows through AWS Managed Workflows for Apache Airflow (MWAA)Develop and optimize data queries using AWS Athena to support efficient data analysisAutomate infrastructure provisioning and deployment processes using Terraform and GitHub ActionsImplement testing, monitoring, troubleshooting, and data-quality controls to ensure pipeline reliabilityParticipate in code reviews and help drive strong engineering best practices across the teamCollaborate with engineering, product, and business teams within an Agile environmentRequirementsA minimum of 3 years of relevant professional experienceStrong core Python programming skills for building data engineering solutionsHands-on experience with Python Pandas for data manipulation and analysisProficiency in PySpark for processing large-scale distributed dataExperience with AWS MWAA or Apache Airflow for orchestrating and managing data workflowsWorking knowledge of AWS Athena for querying and analyzing data stored in AWSExperience using Terraform to automate infrastructure provisioning and managementFamiliarity with GitHub Actions for building automated CI/CD workflowsSolid understanding of DevOps practices applied to data engineering environmentsStrong data engineering, debugging, and problem-solving skillsUpper-intermediate English language skills or higher (B1)Nice to haveExperience using GitHub Copilot to support development, code reviews, testing, and release managementFamiliarity with CI/CD practices and tooling for streamlined software deliveryExperience working within Agile/Scrum environmentsBackground in financial services or investment management industriesExperience with Gen AI application development and applying Gen AI within the software development lifecycle (SDLC)We offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn