Senior Data Engineer

EPAM Systems; Argentina; On-site; ARS 2,000,000 - 3,000,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling and certifications

Global career opportunities

Volunteering opportunities

Job summary

EPAM Systems is seeking a Senior Data Engineer to strengthen our data platform. You will own end-to-end data pipelines, build adapters, and implement resolvers to ensure robust ingestion, lineage, and signals computation across multiple sources.

The role emphasizes schema management, data quality telemetry, and clear communication in English to translate requirements into scalable architectures. Join a globally distributed team delivering AI-enabled data solutions.

Qualifications

• 3+ years of hands-on Python software engineering.
• Experience with AI data engineering in data platforms.
• Proven data pipeline development from design to implementation.
• Hands-on PostgreSQL for storage and querying.
• Knowledge of idempotent ingest, upsert auditing, and replay safety.
• Familiarity with data quality metrics and telemetry.
• Strong English communication to translate requirements into architecture.

Responsibilities

• Execute database migrations across the Unified Data Store for schema consistency.
• Build and maintain source adapters to connect external systems into the data platform.
• Implement Field Mapper and per-project bindings for ingestion normalization.
• Implement Link Resolver for CL-to-ticket and related links feeding the Attribution Resolver.
• Develop Attribution Resolver and Counted Signals Aggregator for provenance and counting.
• Create Area Vocabulary and translation tables for consistent area classification.
• Develop Signal Catalogue jobs for core signals with provenance capture.
• Own data dictionary authorship across storage components.

Skills

Python

Data pipelines

AI data engineering

Machine Learning basics

English (B2+)

Idempotent ingest

Data quality telemetry

Spec-driven development

Tools

Apache Airflow

PostgreSQL

Jira/JaaS API

Job description

We are looking for a Senior Data Engineer to join our team. The Data Engineer is the most data-intensive engineering role on the engagement. If any pipeline drops data, positions drift, or signals compute incorrectly, calibration and UAT break. Correctness and operational robustness here are a prerequisite for everything else.

Responsibilities

• Execute all database migration sets spanning the Unified Data Store to ensure schema consistency across the platform
• Build and maintain the full suite of Source Adapters responsible for connecting external systems into the data platform
• Implement the Field Mapper, establishing per-project and per-franchise field bindings that normalize source system fields into the unified schema during ingestion
• Implement the Link Resolver, responsible for resolving CL-to-ticket, ticket-to-ticket, and case-to-defect/requirement links across all source families, feeding directly into the Attribution Resolver
• Implement the Attribution Resolver, tracing the change-to-ticket-to-area-to-test chain, alongside the Counted Signals Aggregator, which builds file-to-area and area-to-area counted association tables with path normalization and counting verification
• Build the Area Vocabulary and accompanying Translation Tables to support consistent area classification across the system
• Develop all Signal Catalogue computation jobs covering the eight core signals — area fragility, recency, recent failures, change-touch, coupling, windowed area change volume, testing alignment, validation recency, and defect impact/volume/age — ensuring provenance capture throughout
• Take ownership of data dictionary authoring across all storage components, documenting incrementally as new features are delivered

Requirements

• 3+ years of hands-on relevant experience in Python software engineering
• Background in AI Data Engineering, applying data engineering practices to support AI/ML-driven systems
• Practical experience with Apache Airflow for orchestrating and scheduling data workflows
• Working knowledge of Machine Learning concepts and their application within data systems
• Proven experience in data pipeline development, from design through implementation
• Hands-on experience with PostgreSQL for data storage and querying
• Experience designing idempotent ingest processes, including natural keys, upsert auditing, duplicate detection, and replay safety
• Experience integrating multiple heterogeneous data sources into a unified system
• Skilled in data quality and telemetry practices, including fill-rate counters, volume metrics, and reconciliation reporting
• Familiarity with Spec Driven Development methodology
• Decent communication skills with working English fluency (B2 level or higher) to understand business requirements and translate them into agentic architectures

Nice to have

• Experience developing API clients for Perforce or Code Hub
• Experience integrating with the JaaS (Jira) REST API
• Familiarity with test management APIs such as QMetry, Zephyr, or similar tools
• Experience building Snowflake connectors, including key-pair authentication and warehouse extract queries
• Knowledge of temporal data systems and as-of read patterns

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunitiesEPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn