Senior Data Engineer

Senior Data Engineer

📍 Location: Shelton, Connecticut, United States (Hybrid)

🏢 Industry: Restaurants

💼 Work Setting: Hybrid

Are you passionate about building scalable data platforms, designing modern data pipelines, and transforming complex data into powerful business insights?

We are seeking a highly skilled Senior Data Engineer to join a dynamic technology team focused on developing robust data solutions that support enterprise integrations, analytics, and data-driven decision-making. This role is ideal for a hands-on professional who enjoys solving complex data challenges, collaborating across teams, and delivering high-performance cloud-based data solutions.

Key Responsibilities

• Design, develop, and optimize scalable, reliable, and high-performing data pipelines and integration solutions.
• Partner with cross-functional teams to deliver enterprise data integration initiatives with a strong focus on resilience, scalability, and operational excellence.
• Collaborate with business stakeholders to gather requirements, define technical solutions, and provide effort estimations.
• Develop and maintain automated testing, deployment, and monitoring processes for data pipelines.
• Troubleshoot data-related issues, provide technical support, and ensure smooth operation of data platforms and integrations.
• Create and maintain comprehensive technical documentation, including data flows, lineage, architecture, and operational procedures.
• Support production environments by assisting with advanced issue resolution and performance optimization.
• Ensure high standards of data quality, accuracy, and consistency across enterprise data assets.
• Perform data analysis and root-cause investigations to identify and resolve data anomalies.
• Conduct peer code reviews and mentor junior team members on engineering best practices.
• Implement data governance, security, and master data management standards throughout the data lifecycle.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or an equivalent combination of education and experience.
• 5–8 years of experience designing and developing data pipelines, system integrations, and enterprise data solutions.
• At least 3 years of experience working with modern cloud-based data platforms and technologies.
• Strong experience building and managing lakehouse architectures using modern cloud data technologies.
• Proven expertise designing layered data architectures that support analytics-ready datasets and governed data consumption.
• Experience implementing both batch and streaming data processing solutions.
• Hands-on knowledge of ETL/ELT pipeline orchestration frameworks and workflow management tools.
• Advanced proficiency in SQL and Python-based data engineering solutions.
• Strong understanding of data modeling methodologies, including dimensional modeling and analytical schema design.
• Experience optimizing data platform performance through partitioning, clustering, workload tuning, and query optimization.
• Knowledge of data governance, security controls, metadata management, lineage tracking, and access management.
• Familiarity with CI/CD practices, source control systems, automated testing, and deployment pipelines.
• Experience working with cloud ecosystems and data services across major cloud platforms.
• Exposure to AI, machine learning, or generative AI enablement within modern data environments is a plus.
• Excellent communication, collaboration, and stakeholder management skills.

What Success Looks Like

• Delivering scalable and reliable data solutions that support enterprise-wide analytics and integration initiatives.
• Building efficient, maintainable, and automated data pipelines that meet evolving business needs.
• Ensuring data quality, governance, and security standards are consistently maintained.
• Collaborating effectively with technical and business teams to drive successful project outcomes.
• Mentoring team members and contributing to continuous improvement across engineering practices.
• Enabling business users with trusted, accessible, and analytics-ready data.

Compensation & Benefits

• Competitive base salary.
• Performance-based bonus opportunities.
• Comprehensive health and wellness benefits.
• Retirement savings plans with employer contributions, where applicable.
• Tuition reimbursement and professional development support.
• Mobility and work-related allowances.
• Paid holidays and generous time-off programs.
• Community involvement and volunteer opportunities.
• A collaborative environment that supports innovation, growth, and career advancement.