Senior Data Engineer

About the role

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.

Responsibilities

• Design, develop, and maintain scalable data pipelines
• Build and optimize ETL and ELT workflows
• Develop and maintain enterprise data warehouses and data lakes
• Integrate data from multiple internal and external sources
• Improve data quality, reliability, and performance
• Collaborate with analytics, engineering, and business teams
• Optimize SQL queries and large-scale data processing jobs
• Implement data governance and security best practices
• Monitor production data pipelines and troubleshoot issues
• Support cloud-based data platforms and infrastructure
• Mentor junior data engineers and contribute to engineering standards
• Perform additional data engineering responsibilities as assigned

Requirements

• 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

Nice to Have

• AWS, Azure, or Google Cloud certifications
• Experience with Databricks or Delta Lake
• Knowledge of Kubernetes and Docker
• Experience with Infrastructure as Code tools
• Familiarity with CI/CD pipelines and DevOps practices
• Experience leading technical projects or mentoring engineering teams

Benefits

• 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

Pay

The salary range for this role is $110,000 - $150,000 per year, based on experience, technical expertise, certifications, and client hiring needs. Additional compensation and benefits details will be shared during the hiring process.