Senior Data Software Engineer

EPAM Systems; Chile; Remote; CLP 25,000,000 - 38,000,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Learning & certification

Global career opportunities

Volunteer programs

Employee groups

Job summary

EPAM Systems Inc in Chile seeks a Senior Data Software Engineer to architect scalable data solutions powering key business decisions. You will build robust data pipelines, ingest from multiple sources, and write clean, well-tested code.

Collaborate with cross-functional teams, monitor pipeline performance, review code, and drive data architecture standards. Prior experience with PySpark, Delta Lake, and Databricks certification preferred.

Qualifications

• 3+ years of hands-on data engineering experience.
• Strong experience with PySpark and Spark SQL for large-scale pipelines.
• Proficient in Delta Lake and Unity Catalog for storage and governance.
• Experience with data ingestion via Auto Loader and JDBC/CDC.

Responsibilities

• Architect scalable data pipelines enabling reliable data flow across platforms.
• Build data ingestion workflows from diverse source systems.
• Write clean, well-tested code grounded in software engineering.
• Collaborate with cross-functional teams to turn data needs into solutions.
• Monitor pipeline performance and resolve issues to ensure dependability.
• Participate in code reviews to uphold quality standards.
• Diagnose data quality problems and ensure data accuracy across datasets.
• Document technical workflows to help knowledge sharing and onboarding.

Skills

PySpark

Spark SQL

Delta Lake

Unity Catalog

Lakeflow

pytest

Git

Python

SQL

Databricks

Education

Databricks Certification

Tools

Auto Loader

JDBC/CDC

Databricks

DataStage

SQL Server

Job description

We're on the lookout for a Senior Data Software Engineer to come aboard our team. This position is a great match for someone who takes pleasure in architecting durable data solutions that power important business choices. You'll collaborate closely with a group that prioritizes clean, thoroughly tested code and disciplined engineering approaches. For anyone energized by tackling large-scale data problems, this role provides ample opportunity for both growth and meaningful contributionResponsibilitiesArchitect and construct scalable data pipelines that enable dependable data flow across multiple platformsBuild and sustain data ingestion workflows pulling from a range of different source systemsProduce clean, high-performing, thoroughly tested code grounded in solid software engineering principlesPartner with teams across different functions to understand data needs and shape them into working technical solutionsKeep watch over data pipeline performance, stepping in ahead of time to resolve issues and preserve system dependabilityJoin in on code review sessions to help maintain quality benchmarks and spread knowledge throughout the teamDiagnose and fix data quality problems, safeguarding accuracy and consistency across all datasetsHelp drive continuous enhancement of data architecture practices and engineering standardsCreate documentation covering technical workflows and solutions to aid knowledge sharing and new team member onboardingOperate within an agile framework, taking part in sprint planning sessions and other recurring team activitiesRequirementsAt least 3 years of relevant hands-on professional backgroundSolid practical expertise with PySpark and Spark SQL for constructing and processing large-scale data workflowsBackground building and overseeing Lakeflow pipelines and Jobs to support data orchestrationSkilled in using Auto Loader along with JDBC/CDC ingestion approaches, working with sources like DB2 and SQL ServerStrong background with Delta Lake and Unity Catalog for handling data storage and governance needsExperience maintaining data quality standards and performing source reconciliation to ensure dependable, accurate datasetsBackground writing unit tests through pytest to confirm code correctness and reliabilityFamiliarity with Git and Asset Bundles for managing version control and deployment workflowsUpper-intermediate English language skills or higher (B2)Nice to haveBackground working on DataStage migration initiativesExperience extracting data from Dynamics 365/DataverseHolding a Databricks certificationWe 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 LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.