Senior Data Engineer
About The Position
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.
Requirements
- Undergraduate (Bachelor) Degree in MIS, Computer Science, Information Technology required
- 5 - 7 Years of experience developing ETL & System Integration pipelines required
- 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
Nice To Haves
- Certifications in cloud or data engineering platforms
- Familiarity with non-relational databases and OpenSearch technologies
- Exposure to business intelligence tools such as Tableau or Power BI
Responsibilities
- 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.
- 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.
- 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.
Benefits
- Full benefits package
- Generous paid time off
- 401(k) with company match
- Growth and advancement opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
