Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Charleston, South Carolina
Actively hiring, first seen by us 1 day agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
The Senior Data Engineer is responsible for designing, building, and optimizing scalable data pipelines and cloud-based data systems that support analytics and data-driven decision-making across the organization.
In this role, the Senior Data Engineer will collaborate closely with data analysts, scientists, software engineers, and business stakeholders to improve data accessibility, performance, and scalability.
Build and optimize ETL/ELT pipelines across SQL Server, APIs, Yardi and Salesforce
Move and transform data into AWS S3 and Redshift analytics platforms
Run Airflow and AWS Glue orchestration and monitor pipeline reliability and SLAs
Build enterprise datasets and data models with data quality and governance standards
Implement DevOps, CI/CD, Docker and Terraform practices for data infrastructure
The Senior Data Engineer is responsible for designing, building, and optimizing scalable data pipelines and cloud-based data systems that support analytics and data-driven decision-making across the organization. This role requires expertise in data architecture, ETL development, and modern cloud technologies, with a focus on ensuring high-quality, reliable, and efficient data solutions. The ideal candidate will have strong proficiency in Python, SQL, AWS services such as S3 and Redshift. Experience integrating Salesforce data and working with orchestration tools such as Airflow or AWS Glue is also highly valued.
In this role, the Senior Data Engineer will collaborate closely with data analysts, scientists, software engineers, and business stakeholders to improve data accessibility, performance, and scalability. Key responsibilities include developing and maintaining automated ETL frameworks, managing enterprise data products, implementing DevOps and CI/CD practices, and ensuring data quality and governance standards are met. The position also involves researching and adopting emerging technologies to continuously enhance the organization’s data infrastructure and operational efficiency.
Design, develop, optimize, and maintain scalable ETL/ELT pipelines and cloud-based data integrations across enterprise systems, APIs, and operational platforms including Yardi and Salesforce
support the movement and transformation of data from SQL Server and other source systems into AWS-based analytics platforms including Redshift and S3
Airflow and AWS Glue orchestration -Pipeline monitoring, reliability, and SLA management
Develop and maintain enterprise datasets, models, and transformation frameworks
Docker, Terraform, and deployment management
5 - 7 Years of experience developing ETL & System Integration pipelines required
401(k) with company match
5 - 7 Years of experience designing, building, and improving large data models in complex environments required
5 - 7 Years experience with Cloud Technologies like Airflow, Glue, or similar ETL Tools
5 - 7 Years of experience with SQL, Redshift, Snowflake or similar data warehouse solutions required
5 - 7 Years of experience developing complex Python code to support various integration needs
Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 1
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From 10,703 similar postings that came down. Coming down is not always a hire.
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Open jobs by the week we first saw them, last 12 weeks.
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Position Summary The Senior Data Engineer is responsible for designing, building, and optimizing scalable data pipelines and cloud-based data systems that support analytics and data-driven decision-making across the organization. This role requires expertise in data architecture, ETL development, and modern cloud technologies, with a focus on ensuring high-quality, reliable, and efficient data solutions. The ideal candidate will have strong proficiency in Python, SQL, AWS services such as S3 and Redshift. Experience integrating Salesforce data and working with orchestration tools such as Airflow or AWS Glue is also highly valued. In this role, the Senior Data Engineer will collaborate closely with data analysts, scientists, software engineers, and business stakeholders to improve data accessibility, performance, and scalability. Key responsibilities include developing and maintaining automated ETL frameworks, managing enterprise data products, implementing DevOps and CI/CD practices, and ensuring data quality and governance standards are met. The position also involves researching and adopting emerging technologies to continuously enhance the organization’s data infrastructure and operational efficiency.
- 5 - 7 Years of experience with SQL, Redshift, Snowflake or similar data warehouse solutions required - 5 - 7 Years of experience developing complex Python code to support various integration needs Travel
The ideal candidate will possess strong problem-solving abilities, excellent communication skills, and experience working within agile development environments. Preferred qualifications include certifications in cloud or data engineering platforms, familiarity with non-relational databases and OpenSearch technologies, and exposure to business intelligence tools such as Tableau or Power BI. Success in this role will be measured by pipeline performance, data reliability, cross-functional collaboration, and contributions toward innovation and infrastructure optimization. 1. Pipeline Development & Data Integration (50%) Design, develop, optimize, and maintain scalable ETL/ELT pipelines and cloud-based data integrations across enterprise systems, APIs, and operational platforms including Yardi and Salesforce. Build reliable, high-performance workflows that support the movement and transformation of data from SQL Server and other source systems into AWS-based analytics platforms including Redshift and S3. Key Areas: -ETL/ELT pipeline development and optimization -SQL Server, API, Yardi, Salesforce, and third-party integrations -AWS S3 and Redshift data workflows -Airflow and AWS Glue orchestration -Pipeline monitoring, reliability, and SLA management
1. Pipeline Development & Data Integration (50%) Design, develop, optimize, and maintain scalable ETL/ELT pipelines and cloud-based data integrations across enterprise systems, APIs, and operational platforms including Yardi and Salesforce. Build reliable, high-performance workflows that support the movement and transformation of data from SQL Server and other source systems into AWS-based analytics platforms including Redshift and S3. Key Areas: -ETL/ELT pipeline development and optimization -SQL Server, API, Yardi, Salesforce, and third-party integrations -AWS S3 and Redshift data workflows -Airflow and AWS Glue orchestration -Pipeline monitoring, reliability, and SLA management 2. Collaboration with Analytics, Data Science, and Stakeholders and Data Enablement 30% Develop and maintain enterprise datasets, models, and transformation frameworks while partnering with Analytics, Data Science, AI Initiatives, and Business teams to refine requirements, improve data accessibility, and deliver trusted datasets that support reporting, analytics, and operational decision-making.
- 5 - 7 Years experience with Cloud Technologies like Airflow, Glue, or similar ETL Tools - 5 - 7 Years of experience with SQL, Redshift, Snowflake or similar data warehouse solutions required - 5 - 7 Years of experience developing complex Python code to support various integration needs
Key Areas: * Data modeling and warehousing * Data quality, governance, and documentation * Cross-functional collaboration with business, analytics and AI teams * Dataset refinement and business requirements gathering * Support for BI, AI/ML, and operational analytics initiatives 3. Architecture, Strategic Initiatives & Operational Excellence (20%) Contribute to enterprise data platform and strategy through participation in large-scale initiatives, complex integration design, and modernization of data infrastructure. Support scalable and reliable operations through DevOps, automation, CI/CD, and infrastructure management best practices. Key Areas: * Enterprise data architecture and integration design * Strategic technology evaluation and innovation * Infrastructure automation and CI/CD practices * Docker, Terraform, and deployment management * Agile/Scrum participation and operational support Education
In this role, the Senior Data Engineer will collaborate closely with data analysts, scientists, software engineers, and business stakeholders to improve data accessibility, performance, and scalability. Key responsibilities include developing and maintaining automated ETL frameworks, managing enterprise data products, implementing DevOps and CI/CD practices, and ensuring data quality and governance standards are met. The position also involves researching and adopting emerging technologies to continuously enhance the organization’s data infrastructure and operational efficiency. The ideal candidate will possess strong problem-solving abilities, excellent communication skills, and experience working within agile development environments. Preferred qualifications include certifications in cloud or data engineering platforms, familiarity with non-relational databases and OpenSearch technologies, and exposure to business intelligence tools such as Tableau or Power BI. Success in this role will be measured by pipeline performance, data reliability, cross-functional collaboration, and contributions toward innovation and infrastructure optimization. 1. Pipeline Development & Data Integration (50%) Design, develop, optimize, and maintain scalable ETL/ELT pipelines and cloud-based data integrations across enterprise systems, APIs, and operational platforms including Yardi and Salesforce. Build reliable, high-performance workflows that support the movement and transformation of data from SQL Server and other source systems into AWS-based analytics platforms including Redshift and S3.
- 5 - 7 Years of experience designing, building, and improving large data models in complex environments required - 5 - 7 Years experience with Cloud Technologies like Airflow, Glue, or similar ETL Tools - 5 - 7 Years of experience with SQL, Redshift, Snowflake or similar data warehouse solutions required
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Location
Charleston - 997 Morrison Drive, Suite 402Business
We believe home is more than a place to live. It’s where life happens; connections are made, and communities grow. That’s why we’re committed to creating welcoming places where our residents feel at home, and our people have the opportunity to make a meaningful impact.
If you’re ready to be a part of our team, we encourage you to apply.
Job Description
Position Summary
The Senior Data Engineer is responsible for designing, building, and optimizing scalable data pipelines and cloud-based data systems that support analytics and data-driven decision-making across the organization. This role requires expertise in data architecture, ETL development, and modern cloud technologies, with a focus on ensuring high-quality, reliable, and efficient data solutions. The ideal candidate will have strong proficiency in Python, SQL, AWS services such as S3 and Redshift. Experience integrating Salesforce data and working with orchestration tools such as Airflow or AWS Glue is also highly valued.
In this role, the Senior Data Engineer will collaborate closely with data analysts, scientists, software engineers, and business stakeholders to improve data accessibility, performance, and scalability. Key responsibilities include developing and maintaining automated ETL frameworks, managing enterprise data products, implementing DevOps and CI/CD practices, and ensuring data quality and governance standards are met. The position also involves researching and adopting emerging technologies to continuously enhance the organization’s data infrastructure and operational efficiency.
The ideal candidate will possess strong problem-solving abilities, excellent communication skills, and experience working within agile development environments. Preferred qualifications include certifications in cloud or data engineering platforms, familiarity with non-relational databases and OpenSearch technologies, and exposure to business intelligence tools such as Tableau or Power BI. Success in this role will be measured by pipeline performance, data reliability, cross-functional collaboration, and contributions toward innovation and infrastructure optimization.
1. Pipeline Development & Data Integration (50%)
Design, develop, optimize, and maintain scalable ETL/ELT pipelines and cloud-based data integrations across enterprise systems, APIs, and operational platforms including Yardi and Salesforce. Build reliable, high-performance workflows that support the movement and transformation of data from SQL Server and other source systems into AWS-based analytics platforms including Redshift and S3.
Key Areas:
-ETL/ELT pipeline development and optimization
-SQL Server, API, Yardi, Salesforce, and third-party integrations
-AWS S3 and Redshift data workflows
-Airflow and AWS Glue orchestration
-Pipeline monitoring, reliability, and SLA management
2. Collaboration with Analytics, Data Science, and Stakeholders and Data Enablement 30%
Develop and maintain enterprise datasets, models, and transformation frameworks while partnering with Analytics, Data Science, AI Initiatives, and Business teams to refine requirements, improve data accessibility, and deliver trusted datasets that support reporting, analytics, and operational decision-making.
Key Areas:
* Data modeling and warehousing
* Data quality, governance, and documentation
* Cross-functional collaboration with business, analytics and AI teams
* Dataset refinement and business requirements gathering
* Support for BI, AI/ML, and operational analytics initiatives
3. Architecture, Strategic Initiatives & Operational Excellence (20%)
Contribute to enterprise data platform and strategy through participation in large-scale initiatives, complex integration design, and modernization of data infrastructure. Support scalable and reliable operations through DevOps, automation, CI/CD, and infrastructure management best practices.
Key Areas:
* Enterprise data architecture and integration design
* Strategic technology evaluation and innovation
* Infrastructure automation and CI/CD practices
* Docker, Terraform, and deployment management
* Agile/Scrum participation and operational support
Education
Undergraduate (Bachelor) Degree in MIS, Computer Science, Information Technology required
Work Experience
Travel
Travel up to 20% of the time; rarely travel
Great Incentives!
We care about the well-being and work-life balance of our valued associates! To show how much we care, we offer awesome incentives that include:
Equal Opportunity Employer: Minorities/Religion/Sex/Protected Veterans/Disability/Sexual Orientation/Gender Identity/Marital Status/Pregnancy/Age/National Origin/Genetic Information. Drug free workplace
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We are proud to create a diverse environment and are proud to be an equal opportunity employer. We are grateful for your interest in this position, however, only candidates selected for pre-screening will be contacted.Selected passages from the saved posting. Check the full description for conditions and exceptions.
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Charleston, South Carolina
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