Senior Data Engineer: Data Warehouse & Reporting
Chișinău, Moldova
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
Full-time — employment source
Employment type Full Time
Read the full posting
What you’ll work on
Full postingOwn 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.
From the employer’s posting
Key Responsibilities 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.
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.
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.
Tools in this posting
- Python
- SQL
- PostgreSQL
- Airflow
- Power BI
- dbt
- Great_expectations
Source — Tool mentions in context
- 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.
- 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.
- 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.
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
- 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.
- 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.
Nice to have: - dbt or a comparable transformation framework. - Data quality tooling — Great Expectations, Soda, or similar.
- dbt or a comparable transformation framework. - Data quality tooling — Great Expectations, Soda, or similar. - Spark, or columnar and MPP warehouses.
Benefits in the posting
Full benefits wording- Paid time off (PTO) such as sick days and vacation days;
- Employment type
- Full Time
From the employer’s posting.
Job description
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.
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
Monday - Friday from 14:00 till 22:00
Key Responsibilities
- 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.
Skills, Knowledge and Expertise
- 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.
Nice to have:
- 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
Benefits
- Competitive salary package;
- Being part of a international, dynamic work environment;
- Professional development (seminars, courses);
- Paid time off (PTO) such as sick days and vacation days;
Employment type
Full Time
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on utilitiesone.pinpointhq.com. The employer’s form will show what is required.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Chișinău, Moldova
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- Status in our records
- Active
- First seen by us
- Sep 17, 2026
- Recorded sightings
- 76
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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