Sr Data Engineer

A Day in the Life The Senior Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines and workflows that support analytics, business intelligence, machine learning, and software products. This role partners closely with Data Scientists, Engineers, Analysts, Developers, and business stakeholders to deliver trusted, high-quality data solutions that drive operational efficiency and data-driven decision making. As part of a 12-person Data Engineering team, this individual will help build and maintain a single source of truth for enterprise data. The role is heavily focused on the engineering side of the platform, developing and optimizing Silver and Gold layer data assets that support reporting, analytics, and downstream business applications. Anticipated hiring rate starts at: $130,000. Actual base salary will be determined based on work location, relevant experience, skills, qualification and other job related factors. Visa sponsorship is not available for these roles. What You'll Do Design, build, and maintain scalable ETL/ELT pipelines and data workflows. Develop and optimize Silver and Gold layer datasets within a modern data lake architecture. Build data integrations supporting analytics, reporting, machine learning, and operational use cases. Perform data ingestion, cleansing, transformation, migration, and validation activities. Develop automated workflows to improve operational efficiency and data reliability. Ensure data quality, integrity, and performance across enterprise data platforms. Support batch and streaming data processing initiatives. Design, implement, test, and document data pipelines and integrations. Identify opportunities to simplify, automate, and modernize existing data processes. Partner with cross-functional teams to deliver trusted, curated datasets for business consumption. Mentor junior engineers and promote data engineering best practices. Required Qualifications Bachelor's degree in Computer Science, Information Systems, or related field, or equivalent experience. 8+ years of hands-on Data Engineering or ETL development experience. 2+ years of experience working with Data Lakes in a cloud environment. Strong experience building and supporting enterprise-scale ETL/ELT solutions. Hands-on experience with Databricks and/or PySpark. Experience developing and optimizing data pipelines within modern lakehouse architectures. Experience with ETL tools such as Informatica. Experience with event-driven and streaming technologies such as Kafka or Amazon Kinesis. Strong programming skills in Python, Scala, Java, or similar languages. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Experience with Azure and/or AWS cloud platforms. Experience supporting Medallion Architecture, including Silver and Gold layers. Experience improving data quality, governance, and operational efficiency. Experience building streaming and real-time data processing solutions. Agile/Scrum experience. #J-18808-Ljbffr