Data Engineer (вакансія неактивна)

UPTARGET is seeking a Data Engineer to join our growing data and technology team. In this
role, you’ll design, build, and maintain scalable data pipelines and infrastructure that
enable business intelligence, analytics, and machine learning across the organization.

You will work closely with BI, analytics, and engineering teams to ensure that data is
reliable, well-modeled, and available across departments—including eCommerce,
operations, logistics, finance, and marketing. This is a high-impact technical role
focused on building the foundations of a modern, business-aligned data platform.

Key Responsibilities:
— Design, build, and maintain robust ETL/ELT pipelines that ingest data from
diverse systems (ERP, eCom platforms, APIs, files, etc.)
— Develop and optimize data lakes and data warehouse environments (Azure
Synapse, Snowflake, or similar)
— Collaborate with data analysts and business teams to deliver high-quality
datasets and modeling support
— Implement and automate data quality checks, validation routines, and cleansing
procedures
— Monitor and troubleshoot pipeline performance, data delays, or failures
— Contribute to the standardization of schema, documentation, and pipeline
patterns
— Support compliance, governance, and secure access controls

Requirements:
— 5+ years of experience in data engineering or data platform development
— Proficiency with SQL, PLSQL, and working with structured and semi-structured
data (CSV, Parquet, JSON, APIs)
— Experience building and maintaining pipelines using ETL tools or frameworks
(e.g., ADF, SSIS, dbt, Airflow)
— Familiarity with cloud data warehouse platforms such as Azure Synapse,
Snowflake, Redshift, or BigQuery
— Strong communication skills and the ability to work cross-functionally
— A proactive mindset, eager to understand business context and support rapid
iteration

Bonus Points:
— Scripting knowledge in Python or Bash for automation and transformation tasks
— Experience with cloud platforms (Azure, AWS, or GCP)
— Exposure to data streaming tools (Kafka, Kinesis, etc.)
— Understanding of retail data models, product hierarchies, and omni-channel
metrics