Lincoln Financial Services
Sr. Data Engineer
We are seeking an experienced Data Engineer to join our team. The ideal candidate will have deep experience in both Aurora PostgreSQL and Amazon Redshift Databases along with strong knowledge of AWS Services including Glue, Lamda, S3, Athena, and EC2. The responsibilities include building and maintaining scalable data pipelines, optimizing data systems and enabling advanced analytics and reporting across LFD. What you'll be doing: Design, build and maintain robust data pipelines to support business intelligence and analytics. Optimize and manage data storage in Aurora PostgreSQL and Amazon Redshift, ensuring data integrity and performance. Integrate structured and unstructured data from various internal and external sources. Ensure data security, governance, and compliance best practices. Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality datasets. Develop ETL workflows using AWS Glue, Lambda, custom Python, PySpark and SQL based scripts. Monitor and troubleshoot data workflows. Participate in data architecture discussions and help shape data infrastructure strategy on AWS. What we're looking for: Bachelor's degree in Computer Science, Information Systems, Engineering or related field. 7+ years of experience in AWS data engineering or similar role. Strong expertise in Aurora PostgreSQL and Amazon Redshift. Familiarity with DevOps tools (e.g., Pipelines and CloudFormation). Experience working in Agile development environments. Applications for this position will be accepted through October 3, 2025, subject to earlier closure due to applicant volume.
We are seeking an experienced Data Engineer to join our team. The ideal candidate will have deep experience in both Aurora PostgreSQL and Amazon Redshift Databases along with strong knowledge of AWS Services including Glue, Lamda, S3, Athena, and EC2. The responsibilities include building and maintaining scalable data pipelines, optimizing data systems and enabling advanced analytics and reporting across LFD. What you'll be doing: Design, build and maintain robust data pipelines to support business intelligence and analytics. Optimize and manage data storage in Aurora PostgreSQL and Amazon Redshift, ensuring data integrity and performance. Integrate structured and unstructured data from various internal and external sources. Ensure data security, governance, and compliance best practices. Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality datasets. Develop ETL workflows using AWS Glue, Lambda, custom Python, PySpark and SQL based scripts. Monitor and troubleshoot data workflows. Participate in data architecture discussions and help shape data infrastructure strategy on AWS. What we're looking for: Bachelor's degree in Computer Science, Information Systems, Engineering or related field. 7+ years of experience in AWS data engineering or similar role. Strong expertise in Aurora PostgreSQL and Amazon Redshift. Familiarity with DevOps tools (e.g., Pipelines and CloudFormation). Experience working in Agile development environments. Applications for this position will be accepted through October 3, 2025, subject to earlier closure due to applicant volume.