Data Engineer

Responsibilities

• Build and manage automated ETL processes and data pipelines to support data science teams
• Perform data extraction from various structured and unstructured sources including SQL, Oracle, Snowflake, and ERPs
• Execute data preparation tasks including data cleansing, wrangling, and integration to ensure high data quality
• Implement data ingestion processes for machine learning models to generate predictions
• Manage data tagging and annotation using GCP toolsets
• Support data transformation for both supervised and unsupervised model types

Requirements

• 3+ years of experience with SQL (ETL and complex database scripting)
• 3+ years of experience with Python (ETLs and pipelines for Machine Learning)
• 2+ years of experience with Google Cloud Platform (GCP)
• Proven experience in data ingestion, extraction, cleansing, and wrangling
• Proficiency with CI/CD tools (Jenkins, Airflow, or Azure Pipelines) and Git (GitHub/BitBucket)
• Experience with NoSQL databases (e.g., MongoDB, CosmosDB)

Preferred Qualifications

• Experience with Spark and distributed systems for high data volumes
• Knowledge of Big Data technologies such as Hadoop
• Familiarity with Databricks and API management

Benefits

• Professional growth opportunities
• Dynamic work environment
• Attractive benefits plan
• Statutory benefits and superior perks

About the Company

EPAM NEORIS is a Digital accelerator that helps companies enter the future. With 20 years of experience as Digital Partners to some of the largest companies in the world, we employ more than 4,000 professionals across 11 countries. We cultivate a multicultural startup culture focused on innovation and continuous learning to create high-value solutions for our clients.