Senior Data Engineer

Careerscape is supporting a client opening for a Hybrid Senior Data Engineer. This role focuses on designing and maintaining scalable data pipelines, optimizing data infrastructure, building reliable ETL processes, and supporting enterprise analytics initiatives in a hybrid work environment.This is an excellent opportunity for an experienced data professional who is passionate about cloud technologies, big data platforms, automation, and delivering high-quality data solutions that support critical business decisions.The Senior Data Engineer will work closely with data scientists, software engineers, analytics teams, and business stakeholders to build modern data platforms, improve data quality, optimize performance, and ensure secure, reliable access to business data.This role is ideal for candidates interested in data engineering, cloud architecture, analytics engineering, or enterprise data infrastructure.ResponsibilitiesDesign, develop, and maintain scalable data pipelinesBuild and optimize ETL and ELT workflowsDevelop and maintain enterprise data warehouses and data lakesIntegrate data from multiple internal and external sourcesImprove data quality, reliability, and performanceCollaborate with analytics, engineering, and business teamsOptimize SQL queries and large-scale data processing jobsImplement data governance and security best practicesMonitor production data pipelines and troubleshoot issuesSupport cloud-based data platforms and infrastructureMentor junior data engineers and contribute to engineering standardsPerform additional data engineering responsibilities as assignedRequirementsBachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field required5+ years of experience in Data Engineering, Software Engineering, Database Development, or related rolesStrong expertise in SQL and relational database systemsProficiency with Python, Java, or ScalaExperience with Apache Spark, Kafka, Airflow, or similar big data technologiesExperience with AWS, Microsoft Azure, or Google Cloud PlatformExperience building modern ETL/ELT pipelinesKnowledge of data warehouse platforms such as Snowflake, Redshift, BigQuery, or SynapseStrong understanding of data modeling and database optimizationExcellent problem-solving, communication, and collaboration skillsBenefitsHybrid work flexibility within the United StatesCompetitive senior-level compensationMedical, dental, and vision insurancePaid time off, holidays, and sick leave401(k) retirement savings plan with company matchAnnual performance bonusesEquity or stock incentive opportunities where applicableProfessional development and certification reimbursementCareer growth into Lead Data Engineer, Data Engineering Manager, Principal Data Engineer, Data Architect, or Director of Data Engineering rolesCollaborative and innovative engineering environment

• Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field required
• 5+ years of experience in Data Engineering, Software Engineering, Database Development, or related roles
• Strong expertise in SQL and relational database systems
• Proficiency with Python, Java, or Scala
• Experience with Apache Spark, Kafka, Airflow, or similar big data technologies
• Experience with AWS, Microsoft Azure, or Google Cloud Platform
• Experience building modern ETL/ELT pipelines
• Knowledge of data warehouse platforms such as Snowflake, Redshift, BigQuery, or Synapse
• Strong understanding of data modeling and database optimization
• Excellent problem-solving, communication, and collaboration skills

• Hybrid work flexibility within the United States
• Competitive senior-level compensation
• Medical, dental, and vision insurance
• Paid time off, holidays, and sick leave
• 401(k) retirement savings plan with company match
• Annual performance bonuses
• Equity or stock incentive opportunities where applicable
• Professional development and certification reimbursement
• Career growth into Lead Data Engineer, Data Engineering Manager, Principal Data Engineer, Data Architect, or Director of Data Engineering roles
• Collaborative and innovative engineering environment