Senior DWH Engineer – Data Architect

Langate Software

DWH Engineer responsible for defining architecture and building ETL/ELT pipelines for a new Data Platform. Working with modern technologies and large-scale datasets in a flexible part-time schedule.

Posted 7/28/2026part-timeRemote • 🇺🇦 UkraineSeniorWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in designing and implementing scalable Data Warehouse and Data Lake architectures, optimizing ETL/ELT pipelines, and ensuring high-quality data for analytics. Proficient in evaluating modern Data Engineering tools and making architecture decisions to enhance platform performance and cost efficiency.

Highest-signal resume keywords

Data EngineeringData ArchitectureSnowflakeDatabricksETL/ELT Pipeline Development

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 Warehouse DesignData Lake SolutionsBig Data ProcessingSQLData ModelingPerformance OptimizationData Ingestion SolutionsIncremental Data SynchronizationScalable ArchitectureAnalytics-Ready Data

Soft Skills

CollaborationIndependent WorkDecision-Making

Tools & Technologies

SnowflakeDatabricksMicrosoft Fabric

Industry Keywords

ETLELTData Engineering ToolsLarge-Scale DatasetsStakeholder Collaboration

Tech Stack

Tools & technologies

ETLSQL

About the role

Key responsibilities & impact

Design and implement scalable Data Warehouse and Data Lake architectures
Build and optimize ETL/ELT pipelines
Develop data ingestion solutions for multiple third-party SaaS platforms
Process and transform large volumes of structured data
Design incremental data synchronization processes
Evaluate and introduce modern Data Engineering tools and technologies
Optimize platform performance, scalability, and cost efficiency
Collaborate with stakeholders to define the future architecture of the platform
Ensure high-quality, analytics-ready data for reporting and downstream consumer

Requirements

What you’ll need

5+ years of experience in Data Engineering or Data Architecture
Strong commercial experience with Snowflake and/or Databricks or Microsoft Fabric
Experience designing and building Data Warehouse or Data Lake solutions
Hands-on experience with Big Data processing
Strong ETL/ELT pipeline development experience
Excellent SQL skills
Experience working with large-scale datasets (terabytes of data)
Strong understanding of data modeling and performance optimization
Upper-Intermediate+ English
Ability to work independently and make architecture decisions

Benefits

Comp & perks

Flexible Part-Time (approx. 20–25 hours per week)
Agile schedule with the ability to balance daily workload (4–6 hours/day)
No late meetings and overtime
Greenfield architecture with no legacy constraints
Opportunity to build a modern Data Platform from scratch
Freedom to influence technology choices and architectural decisions
Challenging Big Data and distributed data processing problems
High level of ownership and autonomy
Direct impact on a new strategic company initiative
Work with the latest technologies in the Data Engineering ecosystem