Description review
Data Engineer
Get My Course · United States · back to the listing
HR standards
69/100
needs work
Title ↔ description
89/100
strong
Reads as
Data Engineer
100% confident
How others title the same work
Large employers
- Senior Software Engineer - Data Platform Coinbase
- Senior Security Data Engineer Doordash
- Data Engineer, Product Analytics Meta
- Senior Staff Data Engineer Mozilla
- Staff, Analytics Engineer, GTM Data Science & Analytics Twilio
Startups
- Senior Data Engineer Camber
- Cardog | Toronto, Canada or REMOTE | Full-time Cardog
- Connie Health | Senior Analytics Engineer | Boston, MA | HYBRID | $150k-$185k + equity Connie Health
- DoubleVerify (DV Scibids) | Sr. Data Engineer I | ONSITE/HYBRID - New York, NY (3x/week) | Full-time | $89K–$178K DoubleVerify (DV Scibids)
- Forecasting Research Institute (FRI) | Data Engineer | REMOTE | Full-time Forecasting Research Institute (FRI)
What the listing never says
- 16 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
This is a remote position.
Job title: Data Engineer Schedule: Full time; 40 hours per week; Monday to Friday Rate: 60,000 - 100,000 Philippine Pesos per month
We are seeking a highly skilled and experienced Data Engineer to join our Data Engineering team. The ideal candidate will have a strong foundation in data processing and analytics, with specific expertise in Microsoft Azure's Synapse Analytics and Azure Data Factory. You will play a crucial role in developing and optimizing our data pipeline architecture, as well as managing and improving data flow and collection for cross-functional teams. Responsibilities:
• Design, build, and maintain scalable and reliable data pipelines using Azure Synapse Analytics and Azure Data Factory.
• Work closely with stakeholders to understand data requirements and implement systems for large-scale data analysis and reporting.
• Ensure data quality and consistency across data pipelines and implement secure and compliant data handling procedures.
• Collaborate with data scientists and analysts to support data modelling, analysis, and machine learning projects.
• Monitor and optimize performance of data pipelines and databases.
Requirements
• Bachelor’s degree in computer science, Engineering, Mathematics, or a related field (Experience > Education)
• Minimum of 3 years of experience in a data engineering role with a strong focus on Microsoft Azure data services, particularly Azure Synapse Analytics and Azure Data Factory.
• Proven expertise in SQL, Python, and other scripting languages.
• Experience with data modeling, ETL processes, and data warehousing principles.
• Familiarity with Azure Databricks, Azure Data Lake Storage, and other components of the Azure data ecosystem is a plus.
• Strong analytical and problem-solving skills, with the ability to work independently and as part of a team.
• Excellent communication skills, with the ability to convey complex technical information to non-technical stakeholders.
• PowerBI experience is also advantageous.
Benefits
• Permanent work from home
• AU morning shift
• Fun and engaging culture
Originally posted on Himalayas
Job title: Data Engineer Schedule: Full time; 40 hours per week; Monday to Friday Rate: 60,000 - 100,000 Philippine Pesos per month
We are seeking a highly skilled and experienced Data Engineer to join our Data Engineering team. The ideal candidate will have a strong foundation in data processing and analytics, with specific expertise in Microsoft Azure's Synapse Analytics and Azure Data Factory. You will play a crucial role in developing and optimizing our data pipeline architecture, as well as managing and improving data flow and collection for cross-functional teams. Responsibilities:
• Design, build, and maintain scalable and reliable data pipelines using Azure Synapse Analytics and Azure Data Factory.
• Work closely with stakeholders to understand data requirements and implement systems for large-scale data analysis and reporting.
• Ensure data quality and consistency across data pipelines and implement secure and compliant data handling procedures.
• Collaborate with data scientists and analysts to support data modelling, analysis, and machine learning projects.
• Monitor and optimize performance of data pipelines and databases.
Requirements
• Bachelor’s degree in computer science, Engineering, Mathematics, or a related field (Experience > Education)
• Minimum of 3 years of experience in a data engineering role with a strong focus on Microsoft Azure data services, particularly Azure Synapse Analytics and Azure Data Factory.
• Proven expertise in SQL, Python, and other scripting languages.
• Experience with data modeling, ETL processes, and data warehousing principles.
• Familiarity with Azure Databricks, Azure Data Lake Storage, and other components of the Azure data ecosystem is a plus.
• Strong analytical and problem-solving skills, with the ability to work independently and as part of a team.
• Excellent communication skills, with the ability to convey complex technical information to non-technical stakeholders.
• PowerBI experience is also advantageous.
Benefits
• Permanent work from home
• AU morning shift
• Fun and engaging culture
Originally posted on Himalayas