Senior Data Engineer
About The Position
The Senior Data Engineer designs, builds, and optimizes scalable data pipelines and cloud-based data systems that support analytics and data-driven decision-making. The role focuses on data architecture, ETL development, and modern cloud technologies, with an emphasis on high-quality, reliable, and efficient data solutions. It calls for strong proficiency in Python, SQL, and AWS services such as S3 and Redshift; experience integrating Salesforce data and using orchestration tools such as Airflow or AWS Glue is highly valued. The role collaborates with data analysts, data scientists, software engineers, and business stakeholders to improve data accessibility, performance, and scalability. It develops and maintains automated ETL frameworks, manages enterprise data products, implements DevOps and CI/CD practices, and upholds data quality and governance standards. It also researches and adopts emerging technologies to enhance data infrastructure and operational efficiency. The position contributes to enterprise data-platform strategy, large-scale initiatives, complex integration design, and infrastructure modernization. Success is measured by pipeline performance, data reliability, cross-functional collaboration, and contributions to innovation and infrastructure optimization. Travel may be required up to 20% of the time, though travel is described as rare.
Requirements
- Bachelor's degree in MIS, Computer Science, or Information Technology.
- 5–7 years of experience developing ETL and system integration pipelines.
- 5–7 years of experience designing, building, and improving large data models in complex environments.
- 5–7 years of experience with cloud technologies such as Airflow, AWS Glue, or similar ETL tools.
- 5–7 years of experience with SQL and Redshift, Snowflake, or similar data warehouse solutions.
- 5–7 years of experience developing complex Python code to support integration needs.
- Strong problem-solving and communication skills.
- Experience working in Agile development environments.
Nice To Haves
- Experience integrating Salesforce data.
- 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 to move and transform data from SQL Server and other source systems into AWS analytics platforms, including Redshift and S3.
- Develop and maintain enterprise datasets, data models, and transformation frameworks.
- Partner with Analytics, Data Science, AI Initiatives, and Business teams to refine requirements, improve data accessibility, and provide trusted datasets for reporting, analytics, and operational decision-making.
- Support data quality, governance, documentation, BI, AI/ML, and operational analytics initiatives.
- Contribute to enterprise data architecture, integration design, strategic technology evaluation, and data infrastructure modernization.
- Support scalable and reliable operations through DevOps, automation, CI/CD, infrastructure management, Docker, Terraform, and deployment practices.
- Participate in Agile/Scrum processes and operational support.
- Monitor pipeline performance and reliability and manage service-level agreements.
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
