Data Engineer

Sigma Software Group

. Design and develop scalable and reliable data platforms and/or data pipelines for analytical and operational use cases .

Posted 10/12/2026full-timeRemote • UkraineMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing scalable data platforms and pipelines using Azure technologies, with a strong focus on data consistency, quality, and reliability. Proficient in SQL and Python for building data solutions, with experience in modern data architectures and cloud environments.

Highest-signal resume keywords

Data EngineeringAzure Data FactoryApache Spark/PySparkSQLPython

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Pipeline DesignETL/ELT DesignDimensional ModelingData Warehousing PrinciplesDatabase DevelopmentPerformance OptimizationData Lake ArchitecturesWorkflow OrchestrationStreaming Data TechnologiesCI/CD Practices

Soft Skills

CollaborationCommunication

Tools & Technologies

DatabricksAzure SynapseAzure Data Lake StorageAirflowSnowflakeBigQueryRedshiftEvent HubKafkaDelta Lake

Industry Keywords

Data Engineering PracticesCloud Data PlatformsData Processing WorkflowsAgile Development

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAzureBigQueryCloudETLKafkaPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Design and develop scalable and reliable data platforms and/or data pipelines for analytical and operational use cases
Design and implement data processing workflows using distributed processing frameworks such as Apache Spark/pySpark (Databricks)
Contribute to the evolution of the organization’s cloud data platform using Azure technologies, including Azure Data Factory, Synapse, Microsoft Fabric, Databricks, Event Hub, and Azure Data Lake Storage
Integrate and process data from multiple internal and external sources while ensuring data consistency, quality, and reliability
Take ownership of data pipeline reliability, monitoring, and performance
Collaborate with data analysts, data scientists, and engineering teams to translate business and analytical requirements into robust data solutions
Drive improvements in data engineering practices, including pipeline design standards, testing approaches, and operational reliability
Participate in evaluating and introducing new tools and technologies within the data engineering ecosystem

Requirements

What you’ll need

Strong hands-on experience (4+ years) in data engineering or building data processing platforms
Strong SQL skills and solid experience with Python for building and maintaining data pipelines
Experience working with distributed data processing frameworks such as Apache Spark/pySpark (Databricks experience is a strong advantage)
Practical experience designing and implementing data pipelines in cloud environments, preferably within the Azure ecosystem
Experience designing data pipelines and data models for production-scale analytical systems
Strong understanding of data engineering concepts including ETL/ELT design, dimensional modeling, and data warehousing principles
Experience working with modern data lake architectures and data formats such as Parquet and JSON
Experience with workflow orchestration tools (e.g., Airflow)
Experience with database development and performance optimization
Ability to design scalable and maintainable data solutions with minimal supervision
Strong collaboration and communication skills
Professional working proficiency in English
Experience with modern cloud data warehouses such as Snowflake, BigQuery, or Redshift
Experience with streaming data technologies (e.g., Event Hub, Kafka, Spark Streaming)
Experience with Delta Lake or other lakehouse technologies
Familiarity with CI/CD practices and Git-based development workflows
Experience working in agile development environments

Benefits

Comp & perks

Employees can work remotely