Senior Data Engineer: Data Warehouse & Reporting
Utilities One Open · verified Oct 24, 2026 On-site Chișinău Full-time Senior Data Engineering
At a glance
Senior Data Engineering role at Utilities One. Chișinău · full-time.
Pay not stated Data Engineering salary
RoleData Engineering
SenioritySenior
LocationChișinău
WorkplaceOn-site
EmploymentFull-time
PostedSep 17, 2026 · 5w ago
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Run the full flow from source extraction through staging and transformation to published warehouse data
- Shape warehouse layers, data grain, history tracking and incremental loads so changes are handled consistently
- Write and tune PostgreSQL SQL, including the transformations and reporting queries that affect speed
- Build Airflow workflows with reliable schedules, dependencies, retries, safe reruns and backfills
- Check incoming data against sources, work with BI on reporting models, and improve pipeline testing and monitoring
What you bring
- At least six years in data engineering, or backend development with a strong emphasis on data
- Strong Python, hands-on production Airflow, and advanced PostgreSQL SQL skills
- Experience modeling warehouses and building incremental REST API ingestion, including pagination and rate limits
- Fluent Russian, professional English, and practical Power BI knowledge for modeling and report troubleshooting
- Production experience with containers, CI/CD and AI coding tools, plus clear technical documentation skills
Who this fits
This senior role suits an engineer who can own data pipelines in production, set engineering practices and mentor colleagues. It is onsite in Chișinău, Moldova, with a Monday-to-Friday schedule from 14:00 to 22:00. Russian is required for engineering collaboration, with professional English needed for documentation.
From the employer
US Software Solutions is a software development company focused on providing digital technologies to the Utilities, Telecommunications, Energy Efficiency, Renewable Energy, and Gas/Electricity sectors. Thanks to a team consisting exclusively of experts in their field, we are ready to supervise any project, regardless of its complexity and scale.
A Senior Data Engineer responsible for building and managing the company’s data warehouse and reporting infrastructure. The role ensures that data from different systems and APIs is reliably collected, transformed, stored in PostgreSQL, and prepared for accurate and efficient Power BI reporting. In short: they own the data pipeline from source systems to the final reporting layer, while ensuring data quality, performance, reliability, and maintainability. Work schedule:
Monday - Friday from 14:00 till 22:00
A Senior Data Engineer responsible for building and managing the company’s data warehouse and reporting infrastructure. The role ensures that data from different systems and APIs is reliably collected, transformed, stored in PostgreSQL, and prepared for accurate and efficient Power BI reporting. In short: they own the data pipeline from source systems to the final reporting layer, while ensuring data quality, performance, reliability, and maintainability. Work schedule:
Monday - Friday from 14:00 till 22:00
- Own ingestion pipelines from source systems into the warehouse: extraction, staging, transformation, publication.
- Design the warehouse model — layering, grain, incremental load strategy, historization, change handling.
- Write and optimize substantial SQL; transformation logic and reporting-layer performance both live there.
- Build and maintain Airflow DAGs with sound scheduling, dependencies, retries, idempotency, and backfill behavior.
- Integrate new sources, internal and third-party.
- Guarantee data quality — reconciliation against sources, validation, and alerting when a load is wrong, not just when it fails.
- Work with the BI team on the semantic layer and report performance; design upstream models that make reporting straightforward.
- Improve pipeline maintainability, testing, and observability.
- Set data engineering standards and mentor others.
- 6+ years in data engineering, or backend engineering with a heavy data focus.
- Strong Python, and production Airflow experience — DAG design, scheduling semantics, idempotent tasks, backfills, debugging live failures.
- Expert SQL on PostgreSQL: complex analytical queries, execution plans, and knowing why something is slow.
- Solid warehouse modeling — dimensional design, slowly changing dimensions, grain, and incremental patterns.
- Experience building incremental ingestion from REST APIs: pagination, rate limits, retries, late-arriving data.
- Practical data quality discipline — reconciliation, validation, pipelines that fail loudly rather than quietly.
- Working knowledge of Power BI and the Microsoft BI stack; enough to model for it and to debug a slow or incorrect report.
- Containers and CI/CD; able to own your pipelines in production.
- Experience shipping production code with AI coding tools, and the critical eye that comes with it.
- Fluent Russian — engineering collaboration happens in Russian.
- Professional English for documentation.
- Clear technical writing; you can document a model so an analyst uses it without asking you.
- dbt or a comparable transformation framework.
- Data quality tooling — Great Expectations, Soda, or similar.
- Spark, or columnar and MPP warehouses.
- Financial and operational reporting domains
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