Senior Data Software Engineer with AWS and Terraform

EPAM Systems; Georgia; On-site; USD 110,000 - 180,000; Full time

Benefits offered by this job

Relocation opportunities

Global exposure

Career development & certifications

English language training

Stock Purchase Plan

Job summary

EPAM Systems seeks a Senior Data Software Engineer to join a client-facing delivery team focused on building cloud-native data pipelines on AWS. You will ingest and transform large datasets with PySpark on AWS Glue and deliver curated data into Snowflake with strong emphasis on data quality, validation, and reconciliation for downstream analytics.

The role operates with high autonomy, frequent client interaction, and opportunities to influence architecture and data platform modernization across

Qualifications

• 3+ years of experience with Python for production-level data engineering
• Expertise in PySpark for distributed data processing
• Advanced proficiency in Snowflake and data warehousing
• Skills in AWS Glue including job configuration and Data Catalog
• Background in data quality engineering and reconciliation
• Proficiency with AWS services S3, IAM, Lambda, Athena, CloudWatch
• English proficiency at B2 level or higher

Responsibilities

• Design and optimize scalable ETL/ELT pipelines using PySpark on AWS Glue
• Load curated datasets into Snowflake with staging and transformations
• Implement data quality, validation, and reconciliation frameworks
• Develop Python code with unit/integration tests and reusable libraries
• Engage with client stakeholders and provide technical guidance within the workstream
• Coordinate with AWS services for observability, security, and automation
• Participate in code reviews, CI/CD, and documentation

Skills

Python programming

PySpark

Data pipelines

Data quality

AWS

Snowflake

CI/CD

Client communication

Tools

Snowflake

AWS Glue

PySpark

Python

Airflow

Terraform

Job description

We are seeking a Senior Data Software Engineer to join a client-facing delivery team building and hardening cloud-native data pipelines on AWS as part of a data platform modernization program. The role involves ingesting and transforming large datasets with PySpark on AWS Glue and delivering curated, validated data into Snowflake, with a core focus on data quality, validation, and reconciliation for downstream analytics. This position is delivered at a Senior Consultant level with high autonomy and direct client stakeholder communication.

Experience the freedom of remote work from anywhere in Georgia, whether from the comfort of your home, our modern offices in Tbilisi and Batumi or a coworking space in Kutaisi.

Responsibilities

• Design, build, and optimize scalable batch and incremental ETL/ELT pipelines using PySpark on AWS Glue
• Configure Glue jobs, crawlers, triggers, connections, bookmarks, workflows, and the Glue Data Catalog
• Tune workers, partitioning, and shuffle behavior for cost and performance optimization
• Model and load curated datasets into Snowflake with staging, transformation, and publishing layers
• Implement automated data quality and validation frameworks, including schema/contract enforcement and null/uniqueness/referential checks
• Develop row-count and financial reconciliation processes, anomaly detection, and quarantine/reject handling
• Configure and extend Glue Data Quality (DQDL) rules per requirements
• Write clean, modular, testable Python with unit/integration tests and reusable libraries
• Integrate pipelines with AWS services such as S3, IAM, Lambda, Athena, CloudWatch, Step Functions, and Secrets Manager
• Instrument observability through logging, metrics, alerting, and pipeline SLA monitoring
• Participate in code reviews, CI/CD automation, and documentation
• Engage directly with client stakeholders in requirements refinement, design walkthroughs, status reporting, and act as technical advisor within the workstream

Requirements

• 3+ years of experience with Python for production-level data engineering, including OOP and functional patterns
• Expertise in PySpark for distributed data processing and the DataFrame API
• Advanced proficiency in Snowflake, including data warehousing and staging/transformation layers
• Skills in AWS Glue, including job configuration, crawlers, Data Catalog, and DQDL
• Background in data quality engineering, including validation frameworks and reconciliation
• Proficiency in AWS services including S3, IAM, Lambda, Athena, and CloudWatch
• English proficiency at B2 level or higher

Nice to have

• Familiarity with Generative AI / LLM concepts
• Knowledge of Airflow / Step Functions orchestration
• Familiarity with Great Expectations or similar data quality frameworks
• Knowledge of Terraform / CloudFormation

We offer

• We connect like-minded people
  • Delivering innovative solutions to industry leaders, making a global impact
  • Enjoyable working environment, whether it is the vibrant office or the comfort of your own home
  • Opportunity to work abroad for up to two months per year
  • Relocation opportunities within our offices in 55+ countries
  • Corporate and social events
• We invest in your growth
  • Leadership development, career advising, soft skills and well-being programs
  • Certifications, including GCP, Azure and AWS
  • Unlimited access to EPAM's internal learning database
  • Free English classes with certified teachers
• We cover it all
  • Participation in the Employee Stock Purchase Plan
  • Monetary bonuses for engaging in the referral program
  • Comprehensive medical & family care package
  • Five trust days per year (sick leave without a medical certificate)
  • Benefits package (sports activities, a variety of stores and services)

EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.