Описание
EPAM develops enterprise software products, open source solutions, and technology accelerators.
Задачи
•Design, build, and optimize scalable batch and near-real-time ETL/ELT pipelines
•Develop and manage complex workflow orchestrations and automate ingestion routines
•Design and implement data warehouse and lakehouse layers with partitioning, indexing, and SCD Type 2 patterns
•Establish data quality checks and validation frameworks
•Define data requirements, analyze technical constraints, design Source-to-Target Mappings, and make architectural decisions
•Maintain a clean, modular code repository
•Lead code reviews and enforce engineering standards
•Configure CI/CD pipelines with Docker containers
•Deliver technical specifications, metadata lineage documentation, architectural diagrams, and data dictionaries
Требования
•5+ Years of hands-on experience in data engineering, data warehousing, database design, and end-to-end data integration
•Advanced knowledge of cloud integration tools such as Azure Data Factory, AWS Glue, or GCP Dataflow
•Proficiency with Apache Airflow and exposure to CDC or real-time streaming tools such as Kafka and Debezium
•Production-level coding skills in SQL, Python, and PySpark / Apache Spark
•Experience with high-performance databases and cloud-native systems such as Snowflake, ClickHouse, PostgreSQL, MS SQL Server, or Azure Synapse
•Master-level understanding of OLAP, OLTP, Star and Snowflake schemas, Delta Lake/Lakehouse patterns, and data staging processes
•Hands-on experience with Git and automated CI/CD deployment pipelines for data products
•Ability to explain complex technical ideas clearly to business stakeholders and developers
•Fluency in English at Upper-Intermediate level or higher
Nice to have: deep knowledge of dbt and schema validation practices, Docker or Kubernetes experience, serverless ingestion services using AWS Lambda or Azure Functions and RESTful APIs.
Условия
Remote work is available in Georgia and four other locations.
